Stackelberg Network Pricing Games
Briest, Patrick; Krysta, Piotr
2008-01-01
We study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of $m$ priceable edges in a graph. The other edges have a fixed cost. Based on the leader's decision one or more followers optimize a polynomial-time solvable combinatorial minimization problem and choose a minimum cost solution satisfying their requirements based on the fixed costs and the leader's prices. The leader receives as revenue the total amount of prices paid by the followers for priceable edges in their solutions, and the problem is to find revenue maximizing prices. Our model extends several known pricing problems, including single-minded and unit-demand pricing, as well as Stackelberg pricing for certain follower problems like shortest path or minimum spanning tree. Our first main result is a tight analysis of a single-price algorithm for the single follower game, which provides a $(1+\\epsilon) \\log m$-approximation for any $\\epsilon >0$. This can be extended to provide a ...
Huang, Jianwei
2013-01-01
Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing
Trading Network Predicts Stock Price
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi
2014-01-01
Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.
Trading network predicts stock price.
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi
2014-01-16
Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.
Optimal pricing of capacitated networks
Grigoriev, Alexander; Loon, van Joyce; Sitters, René; Uetz, Marc
2009-01-01
We address the algorithmic complexity of a profit maximization problem in capacitated, undirected networks. We are asked to price a set of $m$ capacitated network links to serve a set of $n$ potential customers. Each customer is interested in purchasing a network connection that is specified by a si
Spatial price dynamics: From complex network perspective
Li, Y. L.; Bi, J. T.; Sun, H. J.
2008-10-01
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.
Edge exchangeable models for network data
Crane, Harry
2016-01-01
Exchangeable models for vertex labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distributions observed in many network datasets. Out of this mathematical impossibility emerges the question of how network data can be modeled in a way that reflects known empirical behaviors and respects basic statistical principles. We address this question by observing that edges, not vertices, act as the statistical units in most network datasets, making a theory of edge labeled networks more natural for most applications. Within this context we introduce the new invariance principle of {\\em edge exchangeability}, which unlike its vertex exchangeable counterpart can produce networks with sparse and/or power law structure. We characterize the class of all edge exchangeable network models and identify a particular two parameter family of models with suitable theoretical properties for statistical inference. We discuss issues of estimation from edge exchangeable models and compare our a...
Dynamic pricing by hopfield neural network
Lusajo M Minga; FENG Yu-qiang(冯玉强); LI Yi-jun(李一军); LU Yang(路杨); Kimutai Kimeli
2004-01-01
The increase in the number of shopbots users in e-commerce has triggered flexibility of sellers in their pricing strategies. Sellers see the importance of automated price setting which provides efficient services to a large number of buyers who are using shopbots. This paper studies the characteristic of decreasing energy with time in a continuous model of a Hopfield neural network that is the decreasing of errors in the network with respect to time. The characteristic shows that it is possible to use Hopfield neural network to get the main factor of dynamic pricing; the least variable cost, from production function principles. The least variable cost is obtained by reducing or increasing the input combination factors, and then making the comparison of the network output with the desired output, where the difference between the network output and desired output will be decreasing in the same manner as in the Hopfield neural network energy. Hopfield neural network will simplify the rapid change of prices in e-commerce during transaction that depends on the demand quantity for demand sensitive model of pricing.
Cascading Edge Failures: A Dynamic Network Process
Zhang, June
2016-01-01
This paper considers the dynamics of edges in a network. The Dynamic Bond Percolation (DBP) process models, through stochastic local rules, the dependence of an edge $(a,b)$ in a network on the states of its neighboring edges. Unlike previous models, DBP does not assume statistical independence between different edges. In applications, this means for example that failures of transmission lines in a power grid are not statistically independent, or alternatively, relationships between individuals (dyads) can lead to changes in other dyads in a social network. We consider the time evolution of the probability distribution of the network state, the collective states of all the edges (bonds), and show that it converges to a stationary distribution. We use this distribution to study the emergence of global behaviors like consensus (i.e., catastrophic failure or full recovery of the entire grid) or coexistence (i.e., some failed and some operating substructures in the grid). In particular, we show that, depending on...
Statistical Mechanics of Multi-Edge Networks
Sagarra, Oleguer; Dïaz-Guilera, Albert
2013-01-01
Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There is, however, a subtle difference between networks where weights are continuos variables and those where they account for discrete, distinguishable events, which we call multi-edge networks. In this work we face this problem introducing multi-edge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multi-edges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multi-edge processes. The implications of these results are important as many real agent based problems mapped onto graphs require of this tre...
Price of anarchy on heterogeneous traffic-flow networks
Rose, A.; O'Dea, R.; Hopcraft, K. I.
2016-09-01
The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.
Controlling edge dynamics in complex networks
Nepusz, Tamás
2011-01-01
The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges of a network, and demonstrate that the controllability properties of this process significantly differ from simple nodal dynamics. Evaluation of real-world networks indicates that most of them are more controllable than their randomized counterparts. We also find that transcriptional regulatory networks are particularly easy to control. Analytic calculations show that networks with scale-free degree distributions have better controllability properties than uncorrelated networks, and positively correlated in- and out-degre...
Communication networks for the tactical edge
Evans, Joseph B.; Pennington, Steven G.; Ewy, Benjamin J.
2017-04-01
Information at the tactical level is increasingly critical in today's conflicts. The proliferation of commercial tablets and smart phones has created the ability for extensive information sharing at the tactical edge, beyond the traditional tactical voice communications and location information. This is particularly the case in Gray Zone conflicts, in which tactical decision making and actions are intertwined with information sharing and exploitation. Networking of tactical devices is the key to this information sharing. In this work, we detail and analyze two network models at different parts of the Gray Zone spectrum, and explore a number of networking options including Named Data Networking. We also compare networking approaches in a variety of realistic operating environments. Our results show that Named Data Networking is a good match for the disrupted networking environments found in many tactical situations
Controlling edge dynamics in complex networks
Nepusz, Tamás; Vicsek, Tamás
2012-01-01
The interaction of distinct units in physical, social, biological and technological systems naturally gives rise to complex network structures. Networks have constantly been in the focus of research for the last decade, with considerable advances in the description of their structural and dynamical properties. However, much less effort has been devoted to studying the controllability of the dynamics taking place on them. Here we introduce and evaluate a dynamical process defined on the edges ...
Schaub, Michael T; Yaliraki, Sophia N; Barahona, Mauricio
2013-01-01
The analysis of complex networks has so far revolved mainly around the role of nodes and communities of nodes. However, the dynamics of interconnected systems is commonly focalised on edge processes, and a dual edge-centric perspective can often prove more natural. Here we present graph-theoretical measures to quantify edge-to-edge relations inspired by the notion of flow redistribution induced by edge failures. Our measures, which are related to the pseudo-inverse of the Laplacian of the network, are global and reveal the dynamical interplay between the edges of a network, including potentially non-local interactions. Our framework also allows us to define the embeddedness of an edge, a measure of how strongly an edge features in the weighted cuts of the network. We showcase the general applicability of our edge-centric framework through analyses of the Iberian Power grid, traffic flow in road networks, and the C. elegans neuronal network.
The Price of Anarchy in Cooperative Network Creation Games
Demaine, Erik D; Mahini, Hamid; Zadimoghaddam, Morteza
2009-01-01
In general, the games are played on a host graph, where each node is a selfish independent agent (player) and each edge has a fixed link creation cost \\alpha. Together the agents create a network (a subgraph of the host graph) while selfishly minimizing the link creation costs plus the sum of the distances to all other players (usage cost). In this paper, we pursue two important facets of the network creation game. First, we study extensively a natural version of the game, called the cooperative model, where nodes can collaborate and share the cost of creating any edge in the host graph. We prove the first nontrivial bounds in this model, establishing that the price of anarchy is polylogarithmic in n for all values of α in complete host graphs. This bound is the first result of this type for any version of the network creation game; most previous general upper bounds are polynomial in n. Interestingly, we also show that equilibrium graphs have polylogarithmic diameter for the most natural range of \\a...
Pricing and Referrals in Diffusion on Networks
Leduc, Matt V; Johari, Ramesh
2015-01-01
When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when agents are connected by a network and a monopolist seller chooses a policy to maximize profits. Consumers with low degree (few friends) have incentives to adopt early, while consumers with high degree have incentives to free ride. The seller can induce high degree consumers to adopt early by offering referral incentives - rewards to early adopters whose friends buy in the second period. Referral incentives thus lead to a `double-threshold strategy' by which low and high-degree agents adopt the product early while middle-degree agents wait. We show that referral incentives are optimal on certain networks while intertemporal price discrimination (i.e., a first-period price discount) is optimal on others.
Finding missing edges and communities in incomplete networks
Yan, Bowen; Gregory, Steve
2011-01-01
Many algorithms have been proposed for predicting missing edges in networks, but they do not usually take account of which edges are missing. We focus on networks which have missing edges of the form that is likely to occur in real networks, and compare algorithms that find these missing edges. We also investigate the effect of this kind of missing data on community detection algorithms.
Constant Price of Anarchy in Network Creation Games via Public Service Advertising
Demaine, Erik D.; Zadimoghaddam, Morteza
Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others, without paying much to construct the network. Many generalizations have been considered, including non-uniform interests between nodes, general graphs of allowable edges, bounded budget agents, etc. In all of these settings, there is no known constant bound on the price of anarchy. In fact, in many cases, the price of anarchy can be very large, namely, a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand, the price of stability in all these models is constant, which means that there is chance that agents act selfishly and we end up with a reasonable social cost.
Price of Fairness on Networked Auctions
Mariusz Kaleta
2014-01-01
as follows: no agent can be treated worse than any other in similar circumstances. Ensuring the fairness conditions makes only part of the social welfare available in the auction to be distributed on pure market rules. The rest of welfare must be distributed without market rules and constitutes the so-called price of fairness. We prove that there exists the minimum of price of fairness and that it is achieved when uniform unconstrained market price is used as the base price. The price of fairness takes into account costs of forced offers and compensations for lost profits. The final payments can be different than locational marginal pricing. That means that the widely applied locational marginal pricing mechanism does not in general minimize the price of fairness.
Dynamic Pricing in Electronic Commerce Using Neural Network
Ghose, Tapu Kumar; Tran, Thomas T.
In this paper, we propose an approach where feed-forward neural network is used for dynamically calculating a competitive price of a product in order to maximize sellers’ revenue. In the approach we considered that along with product price other attributes such as product quality, delivery time, after sales service and seller’s reputation contribute in consumers purchase decision. We showed that once the sellers, by using their limited prior knowledge, set an initial price of a product our model adjusts the price automatically with the help of neural network so that sellers’ revenue is maximized.
Using new edges for anomaly detection in computer networks
Neil, Joshua Charles
2017-07-04
Creation of new edges in a network may be used as an indication of a potential attack on the network. Historical data of a frequency with which nodes in a network create and receive new edges may be analyzed. Baseline models of behavior among the edges in the network may be established based on the analysis of the historical data. A new edge that deviates from a respective baseline model by more than a predetermined threshold during a time window may be detected. The new edge may be flagged as potentially anomalous when the deviation from the respective baseline model is detected. Probabilities for both new and existing edges may be obtained for all edges in a path or other subgraph. The probabilities may then be combined to obtain a score for the path or other subgraph. A threshold may be obtained by calculating an empirical distribution of the scores under historical conditions.
Location-Price Competition in Airline Networks
H. Gao
2014-01-01
Full Text Available This paper addresses location-then-price competition in airline market as a two-stage game of n players on the graph. Passenger’s demand distribution is described by multinomial logit model. Equilibrium in price game is computed through best response dynamics. We solve location game using backward induction, knowing that airlines will choose prices from equilibrium for the second-stage game. Some numerical results for airline market under consideration are presented.
The Price of Anarchy in Network Creation Games Is (Mostly) Constant
Mihalák, Matúš; Schlegel, Jan Christoph
We study the price of anarchy and the structure of equilibria in network creation games. A network creation game (first defined and studied by Fabrikant et al. [4]) is played by n players {1,2,...,n}, each identified with a vertex of a graph (network), where the strategy of player i, i = 1,...,n, is to build some edges adjacent to i. The cost of building an edge is α> 0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame (the original variant of Fabrikant et al. [4]) the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame (variant defined and studied by Demaine et al. [3]) the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α > 273·n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α> 129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this (almost) answers one of the basic open problems in the field - is price of anarchy of the network creation game constant for all values of α? - in an affirmative way, up to a tiny range of α.
Spectrum and service pricing for 802.22 networks
Stefan, Andrei Lucian; Rota, Cyril; Pratas, Nuno
2011-01-01
of channels which have an impact on the demand, and thus on the spectrum pricing. The second part of the paper exemplifies how a Bertrand game model can solve the issue of service pricing for a Wireless Regional Area Network (WRAN) operator that is trying to deploy an 802.22 network in a region where...... a competitor already exists. In this work the service pricing was envisioned as a network preplanning step, one that would show the potential revenues for an operator by entering as inputs, among other, the competitor's coverage area and spectrum pricing. The case study has been conducted through CNPT1......, an ongoing cognitive radio network planning tool developed by the authors....
Cooperative Resource Pricing in Service Overlay Networks for Mobile Agents
Nakano, Tadashi; Okaie, Yutaka
The success of peer-to-peer overlay networks depends on cooperation among participating peers. In this paper, we investigate the degree of cooperation among individual peers required to induce globally favorable properties in an overlay network. Specifically, we consider a resource pricing problem in a market-oriented overlay network where participating peers sell own resources (e.g., CPU cycles) to earn energy which represents some money or rewards in the network. In the resource pricing model presented in this paper, each peer sets the price for own resource based on the degree of cooperation; non-cooperative peers attempt to maximize their own energy gains, while cooperative peers maximize the sum of own and neighbors' energy gains. Simulation results are presented to demonstrate that the network topology is an important factor influencing the minimum degree of cooperation required to increase the network-wide global energy gain.
Price discrimination, entry, and switching costs in network competition
Trifunović Dejan
2016-01-01
Full Text Available This paper reviews theoretical models of network competition in telecommunications. We will discuss two alternative approaches. The first approach assumes Hoteling’s horizontal differentiation and the second approach is based on switching costs. We will first analyse spatial competition with linear prices and continue with price discrimination between on-net and off-net calls. Price discrimination can also be used to deter entry to the market. We will also deal with the regulator’s optimal choice of access price, which should be designed to induce entry of new firms. Furthermore, pricing of roaming services and the switching cost approach to network competition will be considered. Finally, we will illustrate the theoretical results with data from the Serbian mobile and fixed telephony market.
Toward edge minability for role mining in bipartite networks
Dong, Lijun; Wang, Yi; Liu, Ran; Pi, Benjie; Wu, Liuyi
2016-11-01
Bipartite network models have been extensively used in information security to automatically generate role-based access control (RBAC) from dataset. This process is called role mining. However, not all the topologies of bipartite networks are suitable for role mining; some edges may even reduce the quality of role mining. This causes unnecessary time consumption as role mining is NP-hard. Therefore, to promote the quality of role mining results, the capability that an edge composes roles with other edges, called the minability of edge, needs to be identified. We tackle the problem from an angle of edge importance in complex networks; that is an edge easily covered by roles is considered to be more important. Based on this idea, the k-shell decomposition of complex networks is extended to reveal the different minability of edges. By this way, a bipartite network can be quickly purified by excluding the low-minability edges from role mining, and thus the quality of role mining can be effectively improved. Extensive experiments via the real-world datasets are conducted to confirm the above claims.
Rate adaptation in ad hoc networks based on pricing
Awuor, F
2011-09-01
Full Text Available to transmit at high power leading to abnormal interference in the network hence degrades network performance (i.e. low data rates, loss of connectivity among others). In this paper, the authors propose rate adaptation based on pricing (RAP) algorithm...
Heterogeneous edge weights promote epidemic diffusion in weighted evolving networks
Duan, Wei; Song, Zhichao; Qiu, Xiaogang
2016-08-01
The impact that the heterogeneities of links’ weights have on epidemic diffusion in weighted networks has received much attention. Investigating how heterogeneous edge weights affect epidemic spread is helpful for disease control. In this paper, we study a Reed-Frost epidemic model in weighted evolving networks. Our results indicate that a higher heterogeneity of edge weights leads to higher epidemic prevalence and epidemic incidence at earlier stage of epidemic diffusion in weighted evolving networks. In addition, weighted evolving scale-free networks come with a higher epidemic prevalence and epidemic incidence than unweighted scale-free networks.
Pricing Resources in LTE Networks through Multiobjective Optimization
Yung-Liang Lai
2014-01-01
Full Text Available The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid “user churn,” which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1 maximizing operator profit and (2 maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.
Pricing resources in LTE networks through multiobjective optimization.
Lai, Yung-Liang; Jiang, Jehn-Ruey
2014-01-01
The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid "user churn," which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.
Dynamic pricing of network goods with boundedly rational consumers.
Radner, Roy; Radunskaya, Ami; Sundararajan, Arun
2014-01-07
We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller's optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product's user base evolving over time and consumers basing their choices on a mixture of a myopic and a "stubborn" expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.
AUTOMATED EDGE DETECTION USING CONVOLUTIONAL NEURAL NETWORK
Mohamed A. El-Sayed
2013-11-01
Full Text Available The edge detection on the images is so important for image processing. It is used in a various fields of applications ranging from real-time video surveillance and traffic management to medical imaging applications. Currently, there is not a single edge detector that has both efficiency and reliability. Traditional differential filter-based algorithms have the advantage of theoretical strictness, but require excessive post-processing. Proposed CNN technique is used to realize edge detection task it takes the advantage of momentum features extraction, it can process any input image of any size with no more training required, the results are very promising when compared to both classical methods and other ANN based methods
Price of anarchy in transportation networks: efficiency and optimality control.
Youn, Hyejin; Gastner, Michael T; Jeong, Hawoong
2008-09-19
Uncoordinated individuals in human society pursuing their personally optimal strategies do not always achieve the social optimum, the most beneficial state to the society as a whole. Instead, strategies form Nash equilibria which are often socially suboptimal. Society, therefore, has to pay a price of anarchy for the lack of coordination among its members. Here we assess this price of anarchy by analyzing the travel times in road networks of several major cities. Our simulation shows that uncoordinated drivers possibly waste a considerable amount of their travel time. Counterintuitively, simply blocking certain streets can partially improve the traffic conditions. We analyze various complex networks and discuss the possibility of similar paradoxes in physics.
Auction pricing of network access for North American railways
Harrod, Steven
2013-01-01
The question of pricing train paths for "open access" railway networks in North America is discussed. An auction process is suggested as necessary to maintain transparency in the contracting process. Multiple random samples of auction pricing for a single track railway line demonstrate that the i...... that the infrastructure entity will receive approximately 15.6% less than the true value of the contracted train paths. This loss of revenue threatens the objective of reducing government subsidy for the railway network. (C) 2012 Elsevier Ltd. All rights reserved....
The price of complexity in financial networks.
Battiston, Stefano; Caldarelli, Guido; May, Robert M; Roukny, Tarik; Stiglitz, Joseph E
2016-09-06
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.
The price of complexity in financial networks
Battiston, Stefano; Caldarelli, Guido; May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.
2016-09-01
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.
The price of complexity in financial networks
May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.
2016-01-01
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises. PMID:27555583
Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices
Kulkarni, Siddhivinayak
2009-01-01
This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...
Optimizing controllability of edge dynamics in complex networks by perturbing network structure
Pang, Shaopeng; Hao, Fei
2017-03-01
Using the minimum input signals to drive the dynamics in complex networks toward some desired state is a fundamental issue in the field of network controllability. For a complex network with the dynamical process defined on its edges, the controllability of this network is optimal if it can be fully controlled by applying one input signal to an arbitrary non-isolated vertex of it. In this paper, the adding-edge strategy and turning-edge strategy are proposed to optimize the controllability by minimum structural perturbations. Simulations and analyses indicate that the minimum number of adding-edges required for the optimal controllability is equal to the minimum number of turning-edges, and networks with positively correlated in- and out-degrees are easier to achieve optimal controllability. Furthermore, both the strategies have the capacity to reveal the relationship between certain structural properties of a complex network and its controllability of edge dynamics.
Edge anisotropy and the geometric perspective on flow networks
Molkenthin, Nora; Tupikina, Liubov; Marwan, Norbert; Donges, Jonathan F; Feudel, Ulrike; Kurths, Jürgen; Donner, Reik V
2016-01-01
Spatial networks have recently attracted great interest in various fields of research. While the traditional network-theoretic viewpoint is commonly restricted to their topological characteristics (often disregarding existing spatial constraints), this work takes a geometric perspective, which considers vertices and edges as objects in a metric space and quantifies the corresponding spatial distribution and alignment. For this purpose, we introduce the concept of edge anisotropy and define a class of measures characterizing the spatial directedness of connections. Specifically, we demonstrate that the local anisotropy of edges incident to a given vertex provides useful information about the local geometry of geophysical flows based on networks constructed from spatio-temporal data, which is complementary to topological characteristics of the same flow networks. Taken both structural and geometric viewpoints together can thus assist the identification of underlying flow structures from observations of scalar v...
Edge anisotropy and the geometric perspective on flow networks
Molkenthin, Nora; Kutza, Hannes; Tupikina, Liubov; Marwan, Norbert; Donges, Jonathan F.; Feudel, Ulrike; Kurths, Jürgen; Donner, Reik V.
2017-03-01
Spatial networks have recently attracted great interest in various fields of research. While the traditional network-theoretic viewpoint is commonly restricted to their topological characteristics (often disregarding the existing spatial constraints), this work takes a geometric perspective, which considers vertices and edges as objects in a metric space and quantifies the corresponding spatial distribution and alignment. For this purpose, we introduce the concept of edge anisotropy and define a class of measures characterizing the spatial directedness of connections. Specifically, we demonstrate that the local anisotropy of edges incident to a given vertex provides useful information about the local geometry of geophysical flows based on networks constructed from spatio-temporal data, which is complementary to topological characteristics of the same flow networks. Taken both structural and geometric viewpoints together can thus assist the identification of underlying flow structures from observations of scalar variables.
On bid-price controls for network revenue management
Bariş Ata
2015-12-01
Full Text Available We consider a network revenue management problem and advance its dual formulation. The dual formulation reveals that the (optimal shadow price of capacity forms a nonnegative martingale. This result is proved under minimal assumptions on network topology and stochastic nature of demand, allowing an arbitrary statistical dependence structure across time and products. Next, we consider a quadratic perturbation of the network revenue management problem and show that a simple (perturbed bid-price control is optimal for the perturbed problem; and it is ε-optimal for the original network revenue management problem. Finally, we consider a predictable version of this control, where the bid prices used in the current period are last updated in the previous period, and provide an upper bound on its optimality gap in terms of the (quadratic variation of demand. Using this upper bound we show that there exists a near-optimal such control in the usual case when periods are small compared to the planning horizon provided that either demand or the incremental information arriving during each period is small. We establish the martingale property of the (near optimal bid prices in both settings. The martingale property can have important implications in practice as it may offer a tool for monitoring the revenue management systems.
Second-best Pricing for Imperfect Substitutes in Urban Networks
Rouwendal, J.; Verhoef, Erik
2003-01-01
This paper considers second-best pricing as it arises through incomplete coverage of full networks. The main principles are first reviewed by considering the classic two-route problem and some extensions that have been studied more recently. In most of these studies the competing routes are assumed
Network Asymmetries and Access Pricing in Cellular Telecommunications
V. Kocsis
2005-01-01
textabstractNetwork shares and retail prices are not symmetric in the telecommunications market with multiple bottlenecks which give rise to new questions of access fee regulation. In this paper we consider a model with two types of asymmetry arising from different entry timing, i.e. a larger reputa
Network Asymmetries and Access Pricing in Cellular Telecommunications
V. Kocsis
2005-01-01
textabstractNetwork shares and retail prices are not symmetric in the telecommunications market with multiple bottlenecks which give rise to new questions of access fee regulation. In this paper we consider a model with two types of asymmetry arising from different entry timing, i.e. a larger reputa
Edge detection of range images using genetic neural networks
FAN Jian-ying; DU Ying; ZHOU Yang; WANG Yang
2009-01-01
Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images was proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters were extracted from range maps as the input nodes of the network in the algorithm. Firstly, a genetic neural network was designed and implemented. The neural network is trained by genetic algorithm, and then genetic neural network algorithm is combined with the virtue of global optimization of genetic algorithm and the virtue of parallel computation of neural network, so that this algorithm is of good global property. The experimental results show that this method can get much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.
Modeling of price and profit in coupled-ring networks
Tangmongkollert, Kittiwat; Suwanna, Sujin
2016-06-01
We study the behaviors of magnetization, price, and profit profiles in ring networks in the presence of the external magnetic field. The Ising model is used to determine the state of each node, which is mapped to the buy-or-sell state in a financial market, where +1 is identified as the buying state, and -1 as the selling state. Price and profit mechanisms are modeled based on the assumption that price should increase if demand is larger than supply, and it should decrease otherwise. We find that the magnetization can be induced between two rings via coupling links, where the induced magnetization strength depends on the number of the coupling links. Consequently, the price behaves linearly with time, where its rate of change depends on the magnetization. The profit grows like a quadratic polynomial with coefficients dependent on the magnetization. If two rings have opposite direction of net spins, the price flows in the direction of the majority spins, and the network with the minority spins gets a loss in profit.
Correlated Edge Overlaps in Multiplex Networks
Baxter, Gareth J; da Costa, Rui A; Dorogovtsev, Sergey N; Mendes, José F F
2016-01-01
We develop the theory of sparse multiplex networks with partially overlapping links based on their local tree-likeness. This theory enables us to find the giant mutually connected component in a two-layer multiplex network with arbitrary correlations between connections of different types. We find that correlations between the overlapping and non-overlapping links markedly change the phase diagram of the system, leading to multiple hybrid phase transitions. For assortative correlations we observe recurrent hybrid phase transitions.
Constructing Edge-Colored Graph for Heterogeneous Networks
侯睿; 武继刚; 陈亚文; 张海波; 隋秀峰
2015-01-01
In order to build a fault-tolerant network, heterogeneous facilities are arranged in the network to prevent homogeneous faults from causing serious damage. This paper uses edge-colored graph to investigate the features of a network topology which is survivable after a set of homogeneous devices malfunction. We propose an approach to designing such networks under arbitrary parameters. We also show that the proposed approach can be used to optimize inter-router connections in network-on-chip to reduce the additional consumption of energy and time delay.
Pricing Strategies for Viral Marketing on Social Networks
Arthur, David
2009-01-01
We study the use of viral marketing strategies on social networks that seek to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. This choice of prices for the buyers is termed as the seller\\'s strategy. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process. © 2009 Springer-Verlag Berlin Heidelberg.
Controllable subspace of edge dynamics in complex networks
Pang, Shao-Peng; Hao, Fei
2017-09-01
For the edge dynamics in some real networks, it may be neither feasible nor necessary to be fully controlled. An accompanying issue is that, when the external signal is applied to a few nodes or even a single node, how many edges can be controlled? In this paper, for the edge dynamics system, we propose a theoretical framework to determine the controllable subspace and calculate its generic dimension based on the integer linear programming. This framework allows us not only to analyze the control centrality, i.e., the ability of a node to control, but also to uncover the controllable centrality, i.e., the propensity of an edge to be controllable. The simulation results and analytic calculation show that dense and homogeneous networks tend to have larger control centrality of nodes and controllable centrality of edges, but the negatively correlated in- and out-degrees of nodes or edges can reduce the two centrality. The positive correlation between the control centrality of node and its out-degree leads to that the distribution of control centrality, instead of that of controllable centrality, is encoded by the out-degree distribution of networks. Meanwhile, the positive correlation indicates that the nodes with high out-degree tend to play more important roles in control.
Robustness of controllability for networks based on edge-attack.
Nie, Sen; Wang, Xuwen; Zhang, Haifeng; Li, Qilang; Wang, Binghong
2014-01-01
We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components.
Application for Single Price Auction Model (SPA) in AC Network
Wachi, Tsunehisa; Fukutome, Suguru; Chen, Luonan; Makino, Yoshinori; Koshimizu, Gentarou
This paper aims to develop a single price auction model with AC transmission network, based on the principle of maximizing social surplus of electricity market. Specifically, we first formulate the auction market as a nonlinear optimization problem, which has almost the same form as the conventional optimal power flow problem, and then propose an algorithm to derive both market clearing price and trade volume of each player even for the case of market-splitting. As indicated in the paper, the proposed approach can be used not only for the price evaluation of auction or bidding market but also for analysis of bidding strategy, congestion effect and other constraints or factors. Several numerical examples are used to demonstrate effectiveness of our method.
Edge orientation for optimizing controllability of complex networks.
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009)], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects.
Pricing strategies for viral marketing on Social Networks
Arthur, David; Sharma, Aneesh; Xu, Ying
2009-01-01
We study the use of viral marketing strategies on social networks to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optim...
Calculating the Price of Anarchy for Network Formation Games
Lichter, Shaun; Friesz, Terry
2011-01-01
There has been recent interest in showing that real networks, designed via optimization, may possess topological properties similar to those investigated by the Network Science community. This suggests that the Network Science community's view that topological properties such as scale-freeness are not the result of some immutable physical laws, but in fact intentional optimization. Recently, it was shown that stable graphs with an arbitrary degree sequence may result from a stability point of a collaborative game. In this paper, we present an integer program (IP) whose solutions yield graphs with a degree sequence, that is closest to a given degree sequence in the Manhattan metric. Stable graphs to the graph formation game and solutions to the IP in this paper, may be non-unique. We relate graphical solutions of the given IP to stable collaboration networks via the price of anarchy which we can calculate exactly as the result of another integer program.
Social networks: Evolving graphs with memory dependent edges
Grindrod, Peter; Parsons, Mark
2011-10-01
The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.
Stock price change rate prediction by utilizing social network activities.
Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito
2014-01-01
Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.
Stock Price Change Rate Prediction by Utilizing Social Network Activities
Mitsubuchi, Takashi; Sakurai, Akito
2014-01-01
Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586
Stock Price Change Rate Prediction by Utilizing Social Network Activities
Shangkun Deng
2014-01-01
Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.
Network Edge Intelligence for the Emerging Next-Generation Internet
Salekul Islam
2010-11-01
Full Text Available The success of the Content Delivery Networks (CDN in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP many opportunities to become directly involved in content and service delivery.
Design of Hierarchical Ring Networks Using Branch-and-Price
Thomadsen, Tommy; Stidsen, Thomas K.
2004-01-01
We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. The hierarchical two layer ring network design problem is solved in two stages: First the bottom layer, i.e. the metro-rings are designed, implicitly taking into account the capacity cost of the federal-ring. Then the federal......-ring is designed connecting the metro-rings, minimizing fixed link establishment costs of the federal-ring. A branch-and-price algorithm is presented for the design of the bottom layer and it is suggested that existing methods are used for the design of the federal-ring. Computational results are given...
Delineating social network data anonymization via random edge perturbation
Xue, Mingqiang
2012-01-01
Social network data analysis raises concerns about the privacy of related entities or individuals. To address this issue, organizations can publish data after simply replacing the identities of individuals with pseudonyms, leaving the overall structure of the social network unchanged. However, it has been shown that attacks based on structural identification (e.g., a walk-based attack) enable an adversary to re-identify selected individuals in an anonymized network. In this paper we explore the capacity of techniques based on random edge perturbation to thwart such attacks. We theoretically establish that any kind of structural identification attack can effectively be prevented using random edge perturbation and show that, surprisingly, important properties of the whole network, as well as of subgraphs thereof, can be accurately calculated and hence data analysis tasks performed on the perturbed data, given that the legitimate data recipient knows the perturbation probability as well. Yet we also examine ways to enhance the walk-based attack, proposing a variant we call probabilistic attack. Nevertheless, we demonstrate that such probabilistic attacks can also be prevented under sufficient perturbation. Eventually, we conduct a thorough theoretical study of the probability of success of any}structural attack as a function of the perturbation probability. Our analysis provides a powerful tool for delineating the identification risk of perturbed social network data; our extensive experiments with synthetic and real datasets confirm our expectations. © 2012 ACM.
Robustness of controllability for networks based on edge-attack.
Sen Nie
Full Text Available We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdős-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components.
Hierarchical Ring Network Design Using Branch-and-Price
Thomadsen, Tommy; Stidsen, Thomas K.
2005-01-01
We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed l...... for jointly solving the clustering problem, the metro ring design problem and the routing problem. Computational results are given for networks with up to 36 nodes.......We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. Hierarchical ring network design problems combines the following optimization problems: Clustering, hub selection, metro ring design, federal ring design and routing problems. In this paper a branch-and-price algorithm is presented...
The Network Completion Problem: Inferring Missing Nodes and Edges in Networks
Kim, M; Leskovec, J
2011-11-14
Network structures, such as social networks, web graphs and networks from systems biology, play important roles in many areas of science and our everyday lives. In order to study the networks one needs to first collect reliable large scale network data. While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomplete with nodes and edges missing. Commonly, only a part of the network can be observed and we would like to infer the unobserved part of the network. We address this issue by studying the Network Completion Problem: Given a network with missing nodes and edges, can we complete the missing part? We cast the problem in the Expectation Maximization (EM) framework where we use the observed part of the network to fit a model of network structure, and then we estimate the missing part of the network using the model, re-estimate the parameters and so on. We combine the EM with the Kronecker graphs model and design a scalable Metropolized Gibbs sampling approach that allows for the estimation of the model parameters as well as the inference about missing nodes and edges of the network. Experiments on synthetic and several real-world networks show that our approach can effectively recover the network even when about half of the nodes in the network are missing. Our algorithm outperforms not only classical link-prediction approaches but also the state of the art Stochastic block modeling approach. Furthermore, our algorithm easily scales to networks with tens of thousands of nodes.
Pricing and Capacity Planning Problems in Energy Transmission Networks
Villumsen, Jonas Christoffer
Efficient use of energy is an increasingly important topic. Environmental and climate concerns as well as concerns for security of supply has made renewable energy sources a viable alternative to traditional energy sources. However, the intermittent nature of for instance wind and solar energy...... necessitates a radical change in the way we plan and operate energy systems. Another paradigm change which began in the 1990’s for electricity systems is that of deregulation. This has led to a variety of different market structures implemented across the world. In this thesis we discuss capacity planning...... and transmission pricing problems in energy transmission networks. Although the modelling framework applies to energy networks in general, most of the applications discussed concern the transmission of electricity. A number of the problems presented involves transmission switching, which allows the operator...
Banerjee, Soumya Jyoti; Roy, Soumen
2014-01-01
There have been many studies on malicious targeting of network nodes using degree, betweenness etc. We propose a new network metric, edge proximity, ${\\cal P}_e$, which demonstrates the importance of specific edges in a network, hitherto not captured by existing network metrics. Effects of removing edges with high ${\\cal P}_e$ might initially seem inconspicuous but is eventually shown to be very harmful for the network. When compared to existing strategies, removal of edges by ${\\cal P}_e$, leads to remarkable increase of diameter and average path length in real and random networks till the first disconnection and beyond. ${\\cal P}_e$ can be consistently used to rupture the network into two nearly equal parts, thus presenting a very potent strategy to greatly harm a network. Targeting by ${\\cal P}_e$ causes notable efficiency loss in US and European power grid. ${\\cal P}_e$ identifies proteins with essential cellular functions in protein-protein interaction networks. It pinpoints regulatory neural connections...
Dynamic supply chain network design with capacity planning and multi-period pricing
Fattahi, Mohammad; Mahootchi, Masoud; Govindan, Kannan
2015-01-01
This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels...
Lambda and the edge of chaos in recurrent neural networks.
Seifter, Jared; Reggia, James A
2015-01-01
The idea that there is an edge of chaos, a region in the space of dynamical systems having special meaning for complex living entities, has a long history in artificial life. The significance of this region was first emphasized in cellular automata models when a single simple measure, λCA, identified it as a transitional region between order and chaos. Here we introduce a parameter λNN that is inspired by λCA but is defined for recurrent neural networks. We show through a series of systematic computational experiments that λNN generally orders the dynamical behaviors of randomly connected/weighted recurrent neural networks in the same way that λCA does for cellular automata. By extending this ordering to larger values of λNN than has typically been done with λCA and cellular automata, we find that a second edge-of-chaos region exists on the opposite side of the chaotic region. These basic results are found to hold under different assumptions about network connectivity, but vary substantially in their details. The results show that the basic concept underlying the lambda parameter can usefully be extended to other types of complex dynamical systems than just cellular automata.
Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network
LI Zhe-min; CUI Li-guo; XU Shi-wei; WENG Ling-yun; DONG Xiao-xia; LI Gan-qiong; YU Hai-peng
2013-01-01
This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China. In the process of determining the structure of the chaotic neural network, the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension, and then the number of hidden layer nodes is estimated by trial and error. Finally, this model is applied to predict the retail prices of eggs and compared with ARIMA. The result shows that the chaotic neural network has better nonlinear iftting ability and higher precision in the prediction of weekly retail price of eggs. The empirical result also shows that the chaotic neural network can be widely used in the ifeld of short-term prediction of agricultural prices.
Building an Early Warning System for Crude Oil Price Using Neural Network
Wonho Song
2010-12-01
Full Text Available In this paper, a crisis index for the oil price shock is defined and a neural network model is specified for the prediction of the crisis index. This paper contributes to the literature in three ways. First, we build an early warning system for crude oil price. Although the oil price became one of the most important price index recently, no research efforts have been made to build an early warning system for crude oil price. Second, the neural network (NN model is used to construct the early warning sysIn this paper, a crisis index for the oil price shock is defined and a neural network model is specified for the prediction of the crisis index. This paper contributes to the literature in three ways. First, we build an early warning system for crude oil price. Although the oil price became one of the most important price index recently, no research efforts have been made to build an early warning system for crude oil price. Second, the neural network (NN model is used to construct the early warning system. Most early warning systems are built based on the signaling approach. In this paper, we show that the neural network models are more flexible and have greater potential as EWS than the signaling approach. Third, we allow the multi-level crisis index. Previous models allowed only a zero/one crisis index whereas our model permits as many levels as possible. With this new model, we try to answer whether the oil price collapse following the historical peak in 2008 was predictable. We compare the results from the NN model with those from the ordered probit (OP model, and show that the oil price crisis and the following crash were predictable by the NN model, but not by the OP model.
Dafny, Leemore S; Hendel, Igal; Marone, Victoria; Ody, Christopher
2017-09-01
Anecdotal reports and systematic research highlight the prevalence of narrow-network plans on the Affordable Care Act's health insurance Marketplaces. At the same time, Marketplace premiums in the period 2014-16 were much lower than projected by the Congressional Budget Office in 2009. Using detailed data on the breadth of both hospital and physician networks, we studied the prevalence of narrow networks and quantified the association between network breadth and premiums. Controlling for many potentially confounding factors, we found that a plan with narrow physician and hospital networks was 16 percent cheaper than a plan with broad networks for both, and that narrowing the breadth of just one type of network was associated with a 6-9 percent decrease in premiums. Narrow-network plans also have a sizable impact on federal outlays, as they depress the premium of the second-lowest-price silver plan, to which subsidy amounts are linked. Holding all else constant, we estimate that federal subsidies would have been 10.8 percent higher in 2014 had Marketplaces required all plans to offer broad provider networks. Narrow networks are a promising source of potential savings for other segments of the commercial insurance market. Project HOPE—The People-to-People Health Foundation, Inc.
Access pricing for transmission networks: Hypotheses and empirical evidence
Martoccia, Maria [Decision Technology Centre, London (United Kingdom)
1999-08-01
The sectors characterised by the use of transmission or transport networks as inputs of production (electricity, gas, telecommunications) have long been considered as natural monopolies. Thanks to the technological innovations which have modified the economics of production (as in electricity generation) or that have driven the development of high value added services (as in telecommunications), the boundaries of the old natural monopolies have been eroded by the presence of operators potentially able to compete in national and international markets. The objective is to delineate, by analysing the more significant theoretical contributions and some of the restructuring experiences of the sector in question, the possible regulatory solutions which, in the perspective of a `European market` for electricity, makes the management and the expansion of the transmission networks adequate for the `open access` of national electricity sectors. The analysis of some mature experiences, such as in Chile, Argentina, the UK and Norway, in the second section, will offer a useful support to this evaluation. The regulatory solution here adopted will be analysed, in particular, with reference to the two main problems outlined above: on the one hand, the problem of providing through prices the necessary information about the opportunities of using the transmission assets; and on the other hand, the problem of defining an efficient incentive mechanism for the behaviour of the monopolist (the owner of the transmission assets). Finally, by considering the limits found in the solutions explored in these models, we will try, in the third section, to delineate the evolution that the regulation of the analysed sectors could follow, in an attempt to make the optimal solution defined in the first section consistent with the imperfections of the real scenarios. (EHS)
Effects of Edge Directions on the Structural Controllability of Complex Networks.
Yandong Xiao
Full Text Available Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain "inappropriate" edge directions. However, the existence of multiple sets of "inappropriate" edge directions suggests that different edges have different effects on optimal controllability-that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions-utilizing only local information-which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.
Effects of Edge Directions on the Structural Controllability of Complex Networks.
Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang
2015-01-01
Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain "inappropriate" edge directions. However, the existence of multiple sets of "inappropriate" edge directions suggests that different edges have different effects on optimal controllability-that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions-utilizing only local information-which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks.
Effects of Edge Directions on the Structural Controllability of Complex Networks
Xiao, Yandong; Lao, Songyang; Hou, Lvlin; Small, Michael; Bai, Liang
2015-01-01
Recent advances indicate that assigning or reversing edge direction can significantly improve the structural controllability of complex networks. For directed networks, approaching the optimal structural controllability can be achieved by detecting and reversing certain “inappropriate” edge directions. However, the existence of multiple sets of “inappropriate” edge directions suggests that different edges have different effects on optimal controllability—that is, different combinations of edges can be reversed to achieve the same structural controllability. Therefore, we classify edges into three categories based on their direction: critical, redundant and intermittent. We then investigate the effects of changing these edge directions on network controllability, and demonstrate that the existence of more critical edge directions implies not only a lower cost of modifying inappropriate edges but also better controllability. Motivated by this finding, we present a simple edge orientation method aimed at producing more critical edge directions—utilizing only local information—which achieves near optimal controllability. Furthermore, we explore the effects of edge direction on the controllability of several real networks. PMID:26281042
Jia, Xiaoliang; An, Haizhong; Sun, Xiaoqi; Huang, Xuan; Gao, Xiangyun
2016-04-01
The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices' mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time-frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.
Visibility graph network analysis of natural gas price: The case of North American market
Sun, Mei; Wang, Yaqi; Gao, Cuixia
2016-11-01
Fluctuations in prices of natural gas significantly affect global economy. Therefore, the research on the characteristics of natural gas price fluctuations, turning points and its influencing cycle on the subsequent price series is of great significance. Global natural gas trade concentrates on three regional markets: the North American market, the European market and the Asia-Pacific market, with North America having the most developed natural gas financial market. In addition, perfect legal supervision and coordinated regulations make the North American market more open and more competitive. This paper focuses on the North American natural gas market specifically. The Henry Hub natural gas spot price time series is converted to a visibility graph network which provides a new direction for macro analysis of time series, and several indicators are investigated: degree and degree distribution, the average shortest path length and community structure. The internal mechanisms underlying price fluctuations are explored through the indicators. The results show that the natural gas prices visibility graph network (NGP-VGN) is of small-world and scale-free properties simultaneously. After random rearrangement of original price time series, the degree distribution of network becomes exponential distribution, different from the original ones. This means that, the original price time series is of long-range negative correlation fractal characteristic. In addition, nodes with large degree correspond to significant geopolitical or economic events. Communities correspond to time cycles in visibility graph network. The cycles of time series and the impact scope of hubs can be found by community structure partition.
The Spectrum Sharing in Cognitive Radio Networks Based on Competitive Price Game
Y. B. Li
2012-09-01
Full Text Available The competitive price game model is used to analyze the spectrum sharing problem in the cognitive radio networks, and the spectrum sharing problem with the constraints of available spectrum resource from primary users is further discussed in this paper. The Rockafeller multiplier method is applied to deal with the constraints of available licensed spectrum resource, and the improved profits function is achieved, which can be used to measure the impact of shared spectrum price strategies on the system profit. However, in the competitive spectrum sharing problem of practical cognitive radio network, primary users have to determine price of the shared spectrum without the acknowledgement of the other primary user’s price strategies. Thus a fast gradient iterative calculation method of equilibrium price is proposed, only with acknowledgement of the price strategies of shared spectrum during last cycle. Through the adaptive iteration at the direction with largest gradient of improved profit function, the equilibrium price strategies can be achieved rapidly. It can also avoid the predefinition of adjustment factor according to the parameters of communication system in conventional linear iteration method. Simulation results show that the proposed competitive price spectrum sharing model can be applied in the cognitive radio networks with constraints of available licensed spectrum, and it has better convergence performance.
牛东晓; 刘达; 邢棉
2008-01-01
A combined model based on principal components analysis (PCA) and generalized regression neural network (GRNN) was adopted to forecast electricity price in day-ahead electricity market. PCA was applied to mine the main influence on day-ahead price, avoiding the strong correlation between the input factors that might influence electricity price, such as the load of the forecasting hour, other history loads and prices, weather and temperature; then GRNN was employed to forecast electricity price according to the main information extracted by PCA. To prove the efficiency of the combined model, a case from PJM (Pennsylvania-New Jersey-Maryland) day-ahead electricity market was evaluated. Compared to back-propagation (BP) neural network and standard GRNN, the combined method reduces the mean absolute percentage error about 3%.
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach
Kang, Xin; Motani, Mehul
2011-01-01
This paper investigates the price-based resource allocation strategies for the uplink transmission of a spectrum-sharing femtocell network, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band as the macrocell. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from the femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and the femtocells subject to a maximum tolerable interference power constraint at the MBS. Especially, two practical femtocell channel models: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas, are investigated. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. Then, the Stackelberg equilibriums for these proposed games are studied, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-...
Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model
Ani Shabri
2014-01-01
Full Text Available A new method based on integrating discrete wavelet transform and artificial neural networks (WANN model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS. The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.
Specification and Validation of an Edge Router Discovery Protocol for Mobile Ad Hoc Networks
Kristensen, Lars Michael; Jensen, Kurt
2004-01-01
We present an industrial project at Ericsson Telebit A/S where Coloured Petri Nets (CP-nets or CPNs) have been used for the design and specification of an edge router discovery protocol for mobile ad-hoc networks. The Edge Router Discovery Protocol (ERDP) supports an edge router in a stationary...... core network in assigning network address prefixes to gateways in mobile ad-hoc networks. This paper focuses on how CP-nets and the CPN computer tools have been applied in the development of ERDP. A CPN model has been constructed that constitutes a formal executable specification of ERDP. Simulation...
Identifying vital edges in Chinese air route network via memetic algorithm
Du, Wen-Bo; Yan, Gang; Lordan, Oriol; Cao, Xian-Bin
2016-01-01
Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems.
Identifying vital edges in Chinese air route network via memetic algorithm
Wenbo Du
2017-02-01
Full Text Available Due to rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges, and hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of the highest topological importance, for which we provide an extensive explanation from the microscope view. Our findings also offer new insights to understanding and optimizing other real-world network systems.
Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.
Luis M Colon-Perez
Full Text Available High spatial and angular resolution diffusion weighted imaging (DWI with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR, edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.
A novel scheme based on minimum delay at the edges for optical burst switching networks
Jinhui Yu(于金辉); Yijun Yang(杨毅军); Yuehua Chen(陈月华); Ge Fan(范戈)
2003-01-01
This paper proposes a novel scheme based on minimum delay at the edges (MDE) for optical burst switching(OBS) networks. This scheme is designed to overcome the long delay at the edge nodes of OBS networks.The MDE scheme features simultaneous burst assembly, channel scheduling, and pre-transmission of controlpacket. It also features estimated setup and explicit release (ESXR) signaling protocol. The MDE schemecan minimize the delay at the edge nodes for data packets, and improve the end-to-end latency performancefor OBS networks. In addition, comparing with the conventional scheme, the performances of the MDEscheme are analyzed in this paper.
Distributed edge detection algorithm based on wavelet transform for wireless video sensor network
Li, Qiulin; Hao, Qun; Song, Yong; Wang, Dongsheng
2011-05-01
Edge detection algorithms are critical to image processing and computer vision. Traditional edge detection algorithms are not suitable for wireless video sensor network (WVSN) in which the nodes are with in limited calculation capability and resources. In this paper, a distributed edge detection algorithm based on wavelet transform designed for WVSN is proposed. Wavelet transform decompose the image into several parts, then the parts are assigned to different nodes through wireless network separately. Each node performs sub-image edge detecting algorithm correspondingly, all the results are sent to sink node, Fusing and Synthesis which include image binary and edge connect are executed in it. And finally output the edge image. Lifting scheme and parallel distributed algorithm are adopted to improve the efficiency, simultaneously, decrease the computational complexity. Experimental results show that this method could achieve higher efficiency and better result.
The Inverse 1-Median Problem on Tree Networks with Variable Real Edge Lengths
Longshu Wu
2013-01-01
Full Text Available Location problems exist in the real world and they mainly deal with finding optimal locations for facilities in a network, such as net servers, hospitals, and shopping centers. The inverse location problem is also often met in practice and has been intensively investigated in the literature. As a typical inverse location problem, the inverse 1-median problem on tree networks with variable real edge lengths is discussed in this paper, which is to modify the edge lengths at minimum total cost such that a given vertex becomes a 1-median of the tree network with respect to the new edge lengths. First, this problem is shown to be solvable in linear time with variable nonnegative edge lengths. For the case when negative edge lengths are allowable, the NP-hardness is proved under Hamming distance, and strongly polynomial time algorithms are presented under l1 and l∞ norms, respectively.
Hybrid Clustering-GWO-NARX neural network technique in predicting stock price
Das, Debashish; Safa Sadiq, Ali; Mirjalili, Seyedali; Noraziah, A.
2017-09-01
Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.
Prediction and Research on Vegetable Price Based on Genetic Algorithm and Neural Network Model
2011-01-01
Considering the complexity of vegetables price forecast,the prediction model of vegetables price was set up by applying the neural network based on genetic algorithm and using the characteristics of genetic algorithm and neural work.Taking mushrooms as an example,the parameters of the model are analyzed through experiment.In the end,the results of genetic algorithm and BP neural network are compared.The results show that the absolute error of prediction data is in the scale of 10%;in the scope that the absolute error in the prediction data is in the scope of 20% and 15%.The accuracy of genetic algorithm based on neutral network is higher than the BP neutral network model,especially the absolute error of prediction data is within the scope of 20%.The accuracy of genetic algorithm based on neural network is obviously better than BP neural network model,which represents the favorable generalization capability of the model.
Energy-Efficient Caching for Mobile Edge Computing in 5G Networks
Zhaohui Luo; Minghui LiWang; Zhijian Lin; Lianfen Huang; Xiaojiang Du; Mohsen Guizani
2017-01-01
Mobile Edge Computing (MEC), which is considered a promising and emerging paradigm to provide caching capabilities in proximity to mobile devices in 5G networks, enables fast, popular content delivery of delay-sensitive...
A quantitative approach to measure road network information based on edge diversity
Wu, Xun; Zhang, Hong; Lan, Tian; Cao, Weiwei; He, Jing
2015-12-01
The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.
Hossein Naderi
2012-08-01
Full Text Available Stock market prediction is one of the most important interesting areas of research in business. Stock markets prediction is normally assumed as tedious task since there are many factors influencing the market. The primary objective of this paper is to forecast trend closing price movement of Tehran Stock Exchange (TSE using financial accounting ratios from year 2003 to year 2008. The proposed study of this paper uses two approaches namely Artificial Neural Networks and multi-layer perceptron. Independent variables are accounting ratios and dependent variable of stock price , so the latter was gathered for the industry of Motor Vehicles and Auto Parts. The results of this study show that neural networks models are useful tools in forecasting stock price movements in emerging markets but multi-layer perception provides better results in term of lowering error terms.
Livi, Lorenzo; Alippi, Cesare
2016-01-01
It is a widely accepted fact that the computational capability of recurrent neural networks is maximized on the so-called "edge of criticality". Once in this configuration, the network performs efficiently on a specific application both in terms of (i) low prediction error and (ii) high short-term memory capacity. Since the behavior of recurrent networks is strongly influenced by the particular input signal driving the dynamics, a universal, application-independent method for determining the edge of criticality is still missing. In this paper, we propose a theoretically motivated method based on Fisher information for determining the edge of criticality in recurrent neural networks. It is proven that Fisher information is maximized for (finite-size) systems operating in such critical regions. However, Fisher information is notoriously difficult to compute and either requires the probability density function or the conditional dependence of the system states with respect to the model parameters. The paper expl...
Mobile ad hoc networking the cutting edge directions
Basagni, Stefano; Giordano, Silvia; Stojmenovic, Ivan
2013-01-01
""An excellent book for those who are interested in learning the current status of research and development . . . [and] who want to get a comprehensive overview of the current state-of-the-art.""-E-Streams This book provides up-to-date information on research and development in the rapidly growing area of networks based on the multihop ad hoc networking paradigm. It reviews all classes of networks that have successfully adopted this paradigm, pointing out how they penetrated the mass market and sparked breakthrough research. Covering both physical issues and applica
The Price of Selfish Stackelberg Leadership in a Network Game
Goldberg, P W
2007-01-01
We study a class of games in which a finite number of agents each controls a quantity of flow to be routed through a network, and are able to split their own flow between multiple paths through the network. Recent work on this model has contrasted the social cost of Nash equilibria with the best possible social cost. Here we show that additional costs are incurred in situations where a selfish ``leader'' agent allocates his flow, and then commits to that choice so that other agents are compelled to minimise their own cost based on the first agent's choice. We find that even in simple networks, the leader can often improve his own cost at the expense of increased social cost. Focusing on the 2-player case, we give upper and lower bounds on the worst-case additional cost incurred.
Stock prices forecasting based on wavelet neural networks with PSO
Wang Kai-Cheng
2017-01-01
Full Text Available This research examines the forecasting performance of wavelet neural network (WNN model using published stock data obtained from Financial Times Stock Exchange (FTSE Taiwan Stock Exchange (TWSE 50 index, also known as Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX, hereinafter referred to as Taiwan 50. Our WNN model uses particle swarm optimization (PSO to choose the appropriate initial network values for different companies. The findings come with two advantages. First, the network initial values are automatically selected instead of being a constant. Second, threshold and training data percentage become constant values, because PSO assists with self-adjustment. We can achieve a success rate over 73% without the necessity to manually adjust parameter or create another math model.
Bi-objective network equilibrium, traffic assignment and road pricing
Wang, JYT; Ehrgott, M
2014-01-01
Multi-objective equilibrium models of traffic assignment state that users of road networks travel on routes that are efficient with respect to several objectives, such as travel time and toll. This concept provides a general framework for modelling traffic flow in tolled road networks. We present the concept of time surplus maximisation as a way of handling user preferences. Given a toll, users have a maximum time they are willing to spend for a trip. Time surplus is this maximum time minus a...
A Round-based Pricing Scheme for Maximizing Service Provider's Revenue in P2PTV Networks
Bhutani, Gitanjali
2009-01-01
In this paper, we analyze a round-based pricing scheme that encourages favorable behavior from users of real-time P2P applications like P2PTV. In the design of pricing schemes, we consider price to be a function of usage and capacity of download/upload streams, and quality of content served. Users are consumers and servers at the same time in such networks, and often exhibit behavior that is unfavorable towards maximization of social benefits. Traditionally, network designers have overcome this difficulty by building-in traffic latencies. However, using simulations, we show that appropriate pricing schemes and usage terms can enable designers to limit required traffic latencies, and be able to earn nearly 30% extra revenue from providing P2PTV services. The service provider adjusts the prices of individual programs incrementally within rounds, while making relatively large-scale adjustments at the end of each round. Through simulations, we show that it is most beneficial for the service provider to carry out ...
Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices
Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro
The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.
Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-hop Relay Networks
Xi, Yufang
2007-01-01
We study a pricing game in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. In this game, each node (1) announces pricing functions which specify the payments it demands from its respective customers depending on the amount of traffic they route to it and (2) allocates the total traffic it receives to its service providers. The profit of a node is the difference between the revenue earned from servicing others and the cost of using others' services. We show that the socially optimal routing of such a game can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its pricing functions or routing decision. On the other hand, there may also exist inefficient equilibria. We characterize the loss of efficiency by deriving the price of anarchy at inefficient equilibria. We show that the price of anarchy is finite for oligopolies with concave marginal cost functions, while it is infinite for general topologies ...
UNITED STABILIZING SCHEME FOR EDGE DELAY IN OPTICAL BURST SWITCHED NETWORKS
无
2006-01-01
A novel scheme, namely united stabilizing scheme for edge delay, is introduced in optical burst switched networks. In the scheme, the limits of burst length and assembly time are both set according to certain qualifications. For executing the scheme, the conception for unit input bit rate is introduced to improve universality, and the assembly algorithm with a buffer safety space under the self-similar traffic model at each ingress edge router is proposed. Then, the components of burst and packet delay are concluded, and the equations that limits of burst length and assembly time should satisfy to stabilize the burst edge delay under different buffer offered loads are educed. The simulation results show that united stabilizing scheme stabilizes both burst and packet edge delay to a great extent when buffer offered load changes from 0.1 to 1, and the edge delay of burst and packet are near the limit values under larger offered load, respectively.
Studying on equilibriums between price and QoS in multi-provider overlay access networks
Wang Yufeng; Wang Wendong
2006-01-01
From the viewpoint of game theory, this paper proposes a model that combines QoS index with price factor in overlay access networks, and uses the multinomial logit (MNL) to model the choice behaviour of users. Each service class is considered an independent and competitive entity offered by each provider,which aims at maximizing its own utility. Based on noncooperative game, we prove the existence and uniqueness of equilibriums between QoS levels and prices among various service classes, and demonstrate the properties of equilibriums. Finally, these results are verified via numerical analysis.
INCITE: Edge-based Traffic Processing and Inference for High-Performance Networks
Baraniuk, Richard G.; Feng, Wu-chun; Cottrell, Les; Knightly, Edward; Nowak, Robert; Riedi, Rolf
2005-06-20
The INCITE (InterNet Control and Inference Tools at the Edge) Project developed on-line tools to characterize and map host and network performance as a function of space, time, application, protocol, and service. In addition to their utility for trouble-shooting problems, these tools will enable a new breed of applications and operating systems that are network aware and resource aware. Launching from the foundation provided our recent leading-edge research on network measurement, multifractal signal analysis, multiscale random fields, and quality of service, our effort consisted of three closely integrated research thrusts that directly attack several key networking challenges of DOE's SciDAC program. These are: Thrust 1, Multiscale traffic analysis and modeling techniques; Thrust 2, Inference and control algorithms for network paths, links, and routers, and Thrust 3, Data collection tools.
Using Artificial Neural Networks to Predict Stock Prices
Kozdraj, Tomasz
2009-01-01
Artificial neural networks constitute one of the most developed conception of artificial intelligence. They are based on pragmatic mathematical theories adopted to tasks resolution. A wide range of their applications also includes financial investments issues. The reason for NN's popularity is mainly connected with their ability to solve complex or not well recognized computational tasks, efficiency in finding solutions as well as the possibility of learning based on patterns or without them....
Edge Detection System using Pulse Mode Neural Network for Image Enhancement
S.Jagadeesh Babu
2012-04-01
Full Text Available Edge detection of an image reduces significantly the amount of data and filters out information that may be regarded as less irrelevant. Edge detection is efficient in medical imaging. Pulse mode neural networks are becoming an attractive solution for function approximation based on frequency modulation. Early pulse mode implementation suffers from some network constraints due to weight range limitations. To provide the best edge detection, the basic algorithm is modified to have pulse mode operations for effective hardware implementation. In this project a new pulse mode network architecture using floating point operations is used in the activation function. By using floating point number system for synapse weight value representation, any function can be approximated by the network. The proposed pulse mode MNN is used to detect the edges in images forming a heterogeneous data base. It shows good learning capability. In addition, four edge detection techniques have been compared. The coding is written in verilog and the final result have been simulated using Xilinx ISE simulator.
Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.
Jin, Junghwan; Kim, Jinsoo
2015-01-01
Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.
Broad edge of chaos in strongly heterogeneous Boolean networks
Lee, Deok-Sun [Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA 02115 (United States); Rieger, Heiko [Theoretische Physik, Universitaet des Saarlandes, 66041 Saarbruecken (Germany)
2008-10-17
The dynamic stability of the Boolean networks representing a model for the gene transcriptional regulation (Kauffman model) is studied by calculating analytically and numerically the Hamming distance between two evolving configurations. This turns out to behave in a universal way close to the phase boundary only for in-degree distributions with a finite second moment. In-degree distributions of the form P{sub d}(k) {approx} k{sup -{gamma}} with 2 < {gamma} < 3, thus having a diverging second moment, lead to a slower increase of the Hamming distance when moving towards the unstable phase and to a broadening of the phase boundary for finite N with decreasing {gamma}. We conclude that the heterogeneous regulatory network connectivity facilitates the balancing between robustness and evolvability in living organisms.
A Game Theoretic Framework for Bandwidth Allocation and Pricing in Federated Wireless Networks
Gu, Bo; Yamori, Kyoko; Xu, Sugang; Tanaka, Yoshiaki
With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.
Mohammad Fathian
2012-04-01
Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.
张闯; 赵洪林; 贾敏
2015-01-01
In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node (ICN) forwards data through participating cooperation node (PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations (CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN’s metric measured by bit-per-Joule and increase the PCN’s revenue.
Xie, Wen-Jie; Li, Ming-Xia; Xu, Hai-Chuan; Chen, Wei; Zhou, Wei-Xing; Stanley, H. Eugene
2016-10-01
Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.
Bayesian Network Modeling to Improve Water Pricing Practices in Northwest China
Yusuyunjiang Mamitimin
2015-10-01
Full Text Available Water pricing is regarded as the most important and simplest economic instrument to encourage more efficient use of irrigation water in crop production. In the extremely water-scarce Tarim River basin in northwest China, improving water use efficiency has high relevance for research and policy. A Bayesian network modeling approach was applied, which is especially suitable under data-scarce conditions and the complex geo-hydrological, socioeconomic, and institutional settings of the study region, as it allows the integration of data from various types of sources. The transdisciplinary approach aimed at understanding the actual water pricing practices, the shortcomings of the current system, and possible ways of improvement. In an iterative procedure of expert interviews and group workshops, the key factors related to water pricing and water use efficiency were identified. The interactions among specific factors were defined by the respective experts, generating a causal network, which describes all relevant aspects of the investigated system. This network was finally populated with probabilistic relationships through a second round of expert interviews and group discussions. The Bayesian modeling exercise was then conducted using Netica software. The modeling results show that the mere increase of water price does not lead to significant increases in water use efficiency in crop production. Additionally, the model suggests a shift to volumetric water pricing, subsidization of water saving irrigation technology, and advancing agricultural extension to enable the farmer to efficiently react to increased costs for water. The applied participatory modeling approach helped to stimulate communication among relevant stakeholders from different domains in the region, which is necessary to create mutual understanding and joint targeted action. Finally, the challenges related to the applied transdisciplinary Bayesian modeling approach are discussed in the
A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES
M. Seidi
2012-01-01
Full Text Available
ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.
AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.
Boivin, Rémi
2014-03-01
Illegal drug prices are extremely high, compared to similar goods. There is, however, considerable variation in value depending on place, market level and type of drugs. A prominent framework for the study of illegal drugs is the "risks and prices" model (Reuter & Kleiman, 1986). Enforcement is seen as a "tax" added to the regular price. In this paper, it is argued that such economic models are not sufficient to explain price variations at country-level. Drug markets are analysed as global trade networks in which a country's position has an impact on various features, including illegal drug prices. This paper uses social network analysis (SNA) to explain price markups between pairs of countries involved in the trafficking of illegal drugs between 1998 and 2007. It aims to explore a simple question: why do prices increase between two countries? Using relational data from various international organizations, separate trade networks were built for cocaine, heroin and cannabis. Wholesale price markups are predicted with measures of supply, demand, risks of seizures, geographic distance and global positioning within the networks. Reported prices (in $US) and purchasing power parity-adjusted values are analysed. Drug prices increase more sharply when drugs are headed to countries where law enforcement imposes higher costs on traffickers. The position and role of a country in global drug markets are also closely associated with the value of drugs. Price markups are lower if the destination country is a transit to large potential markets. Furthermore, price markups for cocaine and heroin are more pronounced when drugs are exported to countries that are better positioned in the legitimate world-economy, suggesting that relations in legal and illegal markets are directed in opposite directions. Consistent with the world-system perspective, evidence is found of coherent world drug markets driven by both local realities and international relations. Copyright © 2013 Elsevier B
Edge Detection Method Based on Neural Networks for COMS MI Images
Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee
2016-12-01
Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.
Effect of edge pruning on structural controllability and observability of complex networks.
Mengiste, Simachew Abebe; Aertsen, Ad; Kumar, Arvind
2015-12-17
Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex systems show dynamic changes in their network connectivity, it is important to understand how perturbations in the connectivity affect the controllability of the system. To this end, we studied the control structure of different types of artificial, social and biological neuronal networks (BNN) as their connections were progressively pruned using four different pruning strategies. We show that the BNNs are more similar to scale-free networks than to small-world networks, when comparing the robustness of their control structure to structural perturbations. We introduce a new graph descriptor, 'the cardinality curve', to quantify the robustness of the control structure of a network to progressive edge pruning. Knowing the susceptibility of control structures to different pruning methods could help design strategies to destroy the control structures of dangerous networks such as epidemic networks. On the other hand, it could help make useful networks more resistant to edge attacks.
Inferring the mesoscale structure of layered, edge-valued, and time-varying networks
Peixoto, Tiago P.
2015-10-01
Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.
Evaluating Link Prediction Accuracy on Dynamic Networks with Added and Removed Edges
Junuthula, Ruthwik R; Devabhaktuni, Vijay K
2016-01-01
The task of predicting future relationships in a social network, known as link prediction, has been studied extensively in the literature. Many link prediction methods have been proposed, ranging from common neighbors to probabilistic models. Recent work by Yang et al. has highlighted several challenges in evaluating link prediction accuracy. In dynamic networks where edges are both added and removed over time, the link prediction problem is more complex and involves predicting both newly added and newly removed edges. This results in new challenges in the evaluation of dynamic link prediction methods, and the recommendations provided by Yang et al. are no longer applicable, because they do not address edge removal. In this paper, we investigate several metrics currently used for evaluating accuracies of dynamic link prediction methods and demonstrate why they can be misleading in many cases. We provide several recommendations on evaluating dynamic link prediction accuracy, including separation into two categ...
Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction
Magdalena Daniela NEMES
2013-01-01
Full Text Available Predicting future prices by using time series forecasting models has become a relevant trading strategy for most stock market players. Intuition and speculation are no longer reliable as many new trading strategies based on artificial intelligence emerge. Data mining represents a good source of information, as it ensures data processing in a convenient manner. Neural networks are considered useful prediction models when designing forecasting strategies. In this paper we present a series of neural networks designed for stock exchange rates forecasting applied on three Romanian stocks traded on the Bucharest Stock Exchange (BSE. A multistep ahead strategy was used in order to predict short-time price fluctuations. Later, the findings of our study can be integrated with an intelligent multi-agent system model which uses data mining and data stream processing techniques for helping users in the decision making process of buying or selling stocks.
A Simulated Annealing Algorithm for Maximum Common Edge Subgraph Detection in Biological Networks
Larsen, Simon; Alkærsig, Frederik G.; Ditzel, Henrik
2016-01-01
introduce a heuristic algorithm for the multiple maximum common edge subgraph problem that is able to detect large common substructures shared across multiple, real-world size networks efficiently. Our algorithm uses a combination of iterated local search, simulated annealing and a pheromone...
BFL: a node and edge betweenness based fast layout algorithm for large scale networks
Kojima Kaname
2009-01-01
Full Text Available Abstract Background Network visualization would serve as a useful first step for analysis. However, current graph layout algorithms for biological pathways are insensitive to biologically important information, e.g. subcellular localization, biological node and graph attributes, or/and not available for large scale networks, e.g. more than 10000 elements. Results To overcome these problems, we propose the use of a biologically important graph metric, betweenness, a measure of network flow. This metric is highly correlated with many biological phenomena such as lethality and clusters. We devise a new fast parallel algorithm calculating betweenness to minimize the preprocessing cost. Using this metric, we also invent a node and edge betweenness based fast layout algorithm (BFL. BFL places the high-betweenness nodes to optimal positions and allows the low-betweenness nodes to reach suboptimal positions. Furthermore, BFL reduces the runtime by combining a sequential insertion algorim with betweenness. For a graph with n nodes, this approach reduces the expected runtime of the algorithm to O(n2 when considering edge crossings, and to O(n log n when considering only density and edge lengths. Conclusion Our BFL algorithm is compared against fast graph layout algorithms and approaches requiring intensive optimizations. For gene networks, we show that our algorithm is faster than all layout algorithms tested while providing readability on par with intensive optimization algorithms. We achieve a 1.4 second runtime for a graph with 4000 nodes and 12000 edges on a standard desktop computer.
The Effect of Edge Definition of Complex Networks on Protein Structure Identification
Jing Sun
2013-01-01
Full Text Available The main objective of this study is to explore the contribution of complex network together with its different definitions of vertexes and edges to describe the structure of proteins. Protein folds into a specific conformation for its function depending on interactions between residues. Consequently, in many studies, a protein structure was treated as a complex system comprised of individual components residues, and edges were interactions between residues. What is the proper time for representing a protein structure as a network? To confirm the effect of different definitions of vertexes and edges in constructing the amino acid interaction networks, protein domains and the structural unit of proteins were described using this method. The identification performance of 2847 proteins with domain/domains proved that the structure of proteins was described well when was around 5.0–7.5 Å, and the optimal cutoff value for constructing the protein structure networks was 5.0 Å ( distances while the ideal community division method was community structure detection based on edge betweenness in this study.
Comparison of canny and V1 neural network based edge detectors applied to road extraction
Hauptfleisch, AC
2006-11-01
Full Text Available The Anti-parallel edge Centerline Extractor (ACE) algorithm is designed to extract road networks from high resolution satellite images. The primary mechanism used by the algorithm to detect the presence of roads is a filter that detects parallel...
Daniel S Himmelstein
2015-07-01
Full Text Available The first decade of Genome Wide Association Studies (GWAS has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks--graphs with multiple node and edge types--for accomplishing both tasks. First we constructed a network with 18 node types--genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database collections--and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as influential mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79 from a withheld multiple sclerosis (MS GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3 validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io. Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach
Huang, Shaojun; Wu, Qiuwei; Oren, Shmuel S.
2015-01-01
This paper presents the distribution locational mar- ginal pricing (DLMP) method through quadratic programming (QP) designed to alleviate the congestion that might occur in a distribution network with high penetration of flexible demands. In the DLMP method, the distribution system operator (DSO...... ensure that the central- ized DSO optimization and the decentralized aggregator optimi- zation converge. Case studies using a distribution network with high penetration of electric vehicles (EVs) and heat pumps (HPs) validate the equivalence of the two optimization setups, and the efficacy...
Jignesh R Parikh
Full Text Available Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.
Parikh, Jignesh R; Xia, Yu; Marto, Jarrod A
2012-01-01
Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.
Analysis of Base Station Assisted Novel Network Design Space for Edge-based WSNs
Muni Venkateswarlu K.
2015-06-01
Full Text Available Limited and constrained energy resources of wireless sensor network should be used wisely to prolong sensor nodes lifetime. To achieve high energy efﬁciency and to increase wireless sensor network lifetime, sensor nodes are grouped together to form clusters. Organizing wireless sensor networks into clusters enables the efﬁcient utilization of limited energy resources of the deployed sensor nodes. However, the problems of unbalanced energy consumption exist in intra and inter cluster communication, and it is tightly bound to the role and the location of a sensor nodes and cluster heads in the network. Also, clustering mechanism results in an unequal load distribution in the network. This paper presents an analytical and conceptual model of Energy-efﬁcient edge-based network partitioning scheme proposed for wireless sensor networks. Also, it analyzes different network design space proposed for wireless sensor networks and evaluates their performance. From the experimental results it is observed that, with proper network organization mechanism, sensor network resources are utilized effectively to elevate network lifetime.
Price-based Energy Control for V2G Networks in the Industrial Smart Grid
Rong Yu
2015-08-01
Full Text Available The energy crisis and global warming call for a new industrial revolution in production and distribution of renewable energy. Distributed power generation will be well developed in the new smart electricity distribution grid, in which robust power distribution will be the key technology. In this paper, we present a new vehicle-to-grid (V2G network for energy transfer, in which distributed renewable energy helps the power grid balance demand and supply. Plug-in hybrid electric vehicles (PHEVs will act as transporters of electricity for distributed renewable energy dispatching. We formulate and analyze the V2G network within the theoretical framework of complex network. We also employ the generalized synchronization method to study the dynamic behavior of V2G networks. Furthermore, we develop a new price-based energy control method to stimulate the PHEV's behavior of charging and discharging. Simulation results indicate that the V2G network can achieve synchronization and each region is able to balance energy supply and demand through price-based control.
Average weighted trapping time of the node- and edge- weighted fractal networks
Dai, Meifeng; Ye, Dandan; Hou, Jie; Xi, Lifeng; Su, Weiyi
2016-10-01
In this paper, we study the trapping problem in the node- and edge- weighted fractal networks with the underlying geometries, focusing on a particular case with a perfect trap located at the central node. We derive the exact analytic formulas of the average weighted trapping time (AWTT), the average of node-to-trap mean weighted first-passage time over the whole networks, in terms of the network size Ng, the number of copies s, the node-weight factor w and the edge-weight factor r. The obtained result displays that in the large network, the AWTT grows as a power-law function of the network size Ng with the exponent, represented by θ(s , r , w) =logs(srw2) when srw2 ≠ 1. Especially when srw2 = 1 , AWTT grows with increasing order Ng as log Ng. This also means that the efficiency of the trapping process depend on three main parameters: the number of copies s > 1, node-weight factor 0 < w ≤ 1, and edge-weight factor 0 < r ≤ 1. The smaller the value of srw2 is, the more efficient the trapping process is.
Multi-operator collaboration for green cellular networks under roaming price consideration
Ghazzai, Hakim
2014-09-01
This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks. Our framework studies the case of LTE-Advanced networks deployed in the same area and owning renewable energy generators. The objective is to reduce the CO2 emissions of cellular networks via collaborative techniques and using base station sleeping strategy while respecting the network quality of service. Low complexity and practical algorithm is employed to achieve green goals during low traffic periods. Cooperation decision criteria are also established basing on derived roaming prices and profit gains of competitive mobile operators. Our numerical results show a significant save in terms of CO2 compared to the non-collaboration case and that cooperative mobile operator exploiting renewables are more awarded than traditional operators.
Matsypura, Dmytro
In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following
Power Allocation and Pricing in Multi-User Relay Networks Using Stackelberg and Bargaining Games
Cao, Qian; Jing, Yindi
2012-01-01
This paper considers a multi-user single-relay wireless network, where the relay gets paid for helping the users forward signals, and the users pay to receive the relay service. We study the relay power allocation and pricing problems, and model the interaction between the users and the relay as a two-level Stackelberg game. In this game, the relay, modeled as the service provider and the leader of the game, sets the relay price to maximize its revenue; while the users are modeled as customers and the followers who buy power from the relay for higher transmission rates. We use a bargaining game to model the negotiation among users to achieve a fair allocation of the relay power. Based on the proposed fair relay power allocation rule, the optimal relay power price that maximizes the relay revenue is derived analytically. Simulation shows that the proposed power allocation scheme achieves higher network sum-rate and relay revenue than the even power allocation. Furthermore, compared with the sum-rate-optimal so...
Inferring the mesoscale structure of layered, edge-valued and time-varying networks
Peixoto, Tiago P
2015-01-01
Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges or as a time-dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e. the use of overly-complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attr...
Optimization of controllability and robustness of complex networks by edge directionality
Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen
2016-09-01
Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.
On Network-Error Correcting Convolutional Codes under the BSC Edge Error Model
Prasad, K
2010-01-01
Convolutional network-error correcting codes (CNECCs) are known to provide error correcting capability in acyclic instantaneous networks within the network coding paradigm under small field size conditions. In this work, we investigate the performance of CNECCs under the error model of the network where the edges are assumed to be statistically independent binary symmetric channels, each with the same probability of error $p_e$($0\\leq p_e<0.5$). We obtain bounds on the performance of such CNECCs based on a modified generating function (the transfer function) of the CNECCs. For a given network, we derive a mathematical condition on how small $p_e$ should be so that only single edge network-errors need to be accounted for, thus reducing the complexity of evaluating the probability of error of any CNECC. Simulations indicate that convolutional codes are required to possess different properties to achieve good performance in low $p_e$ and high $p_e$ regimes. For the low $p_e$ regime, convolutional codes with g...
Duan, Gaopeng; Xiao, Feng; Wang, Long
2017-01-23
This paper focuses on the average consensus of double-integrator networked systems based on the asynchronous periodic edge-event triggered control. The asynchronous property lies in the edge event-detecting procedure. For different edges, their event detections are performed at different times and the corresponding events occur independently of each other. When an event is activated, the two adjacent agents connected by the corresponding link sample their relative state information and update their controllers. The application of incidence matrix facilitates the transformation of control objects from the agent-based to the edge-based. Practically, due to the constraints of network bandwidth and communication distance, agents usually cannot receive the instantaneous information of some others, which has an impact on the system performance. Hence, it is necessary to investigate the presence of communication time delays. For double-integrator multiagent systems with and without communication time delays, the average state consensus can be asynchronously achieved by designing appropriate parameters under the proposed event-detecting rules. The presented results specify the relationship among the maximum allowable time delays, interaction topologies, and event-detecting periods. Furthermore, the proposed protocols have the advantages of reduced communication costs and controller-updating costs. Simulation examples are given to illustrate the proposed theoretical results.
INGRESS FILTERING AT EDGE NETWORK TO PROTECT VPN SERVICE FROM DOS ATTACK
S.Saraswathi
2012-05-01
Full Text Available Internet Protocol (IP examines only the packet header to forward the packet but it does not examine the data in it. As internet is open to public, the seeking for sensitive data by the attacker has increased. It has become a necessity to protect data through the Internet. Virtual Private Network (VPN is a popular service to logically construct private network using the existing public infrastructure. It helps in constructing a geographically dispersed LAN that can securely communicate data using the Internet as the backbone communication network. IP Security (IPSec VPN provides confidentiality, integrity and availability through tunnelling and encryption. IPSec protocol provides various security features but it does not provide any protection against Denial of Service (DoS attack. DoS attacks to VPN represent a serious threat to enterprises operating over the Internet. It also hinders the services provided by the service providers. Malicious traffic enters into the Internet only through the edge network. To provide an uninterrupted VPN service, a protection mechanism is to be added at the edge network. This paper discusses such protection mechanisms based on filtering and cryptographic technique
APPLYING ARTIFICIAL NEURAL NETWORK OPTIMIZED BY FIREWORKS ALGORITHM FOR STOCK PRICE ESTIMATION
Khuat Thanh Tung
2016-04-01
Full Text Available Stock prediction is to determine the future value of a company stock dealt on an exchange. It plays a crucial role to raise the profit gained by firms and investors. Over the past few years, many methods have been developed in which plenty of efforts focus on the machine learning framework achieving the promising results. In this paper, an approach based on Artificial Neural Network (ANN optimized by Fireworks algorithm and data preprocessing by Haar Wavelet is applied to estimate the stock prices. The system was trained and tested with real data of various companies collected from Yahoo Finance. The obtained results are encouraging.
Cognitive Mobile Virtual Network Operator: Investment and Pricing with Supply Uncertainty
Duan, Lingjie; Shou, Biying
2009-01-01
This paper presents the first analytical study of optimal investment and pricing decisions of a cognitive mobile virtual network operator (C-MVNO) under spectrum supply uncertainty. Compared with a traditional MVNO who often leases spectrum via long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by both sensing the empty ``spectrum holes'' of licensed bands and leasing from the spectrum owner. As a result, a C-MVNO can make flexible investment and pricing decisions to match the current demands of the secondary unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is typically cheaper, but the obtained useful spectrum amount is random due to primary licensed users' stochastic traffic. The C-MVNO needs to determine the optimal amounts of spectrum sensing and leasing by evaluating the trade-off between cost and uncertainty. The C-MVNO also needs to determine the optimal price to sell the spectrum to the secondary unlicensed users, taking into account wireless heterogen...
Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.
Junghwan Jin
Full Text Available Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.
Guiling Wu; Jianping Chen; Xinwang Li; Junfeng Chen
2003-01-01
A scheduling algorithm for the edge nodes of optical burst switching (OBS) networks is proposed to guarantee the delay re quirement of services with different CoS (Class of Service) and provide lower burst loss ratio at the same time. The performance of edge nodes based on the proposed algorithm is presented.
Xia, Mingrui; Lin, Qixiang; Bi, Yanchao; He, Yong
2016-01-01
White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.
Mingrui eXia
2016-04-01
Full Text Available White matter (WM tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption and topological contributions to the brain’s network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain’s hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.
Mapping edge-based traffic measurements onto the internal links in MPLS network
Zhao, Guofeng; Tang, Hong; Zhang, Yi
2004-09-01
Applying multi-protocol label switching techniques to IP-based backbone for traffic engineering goals has shown advantageous. Obtaining a volume of load on each internal link of the network is crucial for traffic engineering applying. Though collecting can be available for each link, such as applying traditional SNMP scheme, the approach may cause heavy processing load and sharply degrade the throughput of the core routers. Then monitoring merely at the edge of the network and mapping the measurements onto the core provides a good alternative way. In this paper, we explore a scheme for traffic mapping with edge-based measurements in MPLS network. It is supposed that the volume of traffic on each internal link over the domain would be mapped onto by measurements available only at ingress nodes. We apply path-based measurements at ingress nodes without enabling measurements in the core of the network. We propose a method that can infer a path from the ingress to the egress node using label distribution protocol without collecting routing data from core routers. Based on flow theory and queuing theory, we prove that our approach is effective and present the algorithm for traffic mapping. We also show performance simulation results that indicate potential of our approach.
Competitive closed-loop supply chain network design with price-dependent demands
Rezapour, Shabnam; Farahani, Reza Zanjirani; Fahimnia, Behnam
2015-01-01
Abstract This paper presents a bi-level model for the strategic reverse network design (upper level) and tactical/operational planning (lower level) of a closed-loop single-period supply chain operating in a competitive environment with price-dependent market demand. An existing supply chain (SC...... for the supply of new and remanufactured products. The performance behaviors of both SCs are evaluated with specific focus placed on investigating the impacts of the strategic facility location decisions of the new SC on the tactical/operational transport and inventory decisions of the overall network. The bi......) is involved in the manufacturing and distribution of new products, while the new (to-be-designed) rival SC can supply both new and remanufactured products. Competitions exist not only externally between the two chains supplying new products to the same market, but also internally in the new chain...
Critical Space-Time Networks and Geometric Phase Transitions from Frustrated Edge Antiferromagnetism
Trugenberger, Carlo A
2015-01-01
Recently I proposed a simple dynamical network model for discrete space-time which self-organizes as a graph with Hausdorff dimension d_H=4. The model has a geometric quantum phase transition with disorder parameter (d_H-d_s) where d_s is the spectral dimension of the dynamical graph. Self-organization in this network model is based on a competition between a ferromagnetic Ising model for vertices and an antiferromagnetic Ising model for edges. In this paper I solve a toy version of this model defined on a bipartite graph in the mean field approximation. I show that the geometric phase transition corresponds exactly to the antiferromagnetic transition for edges, the dimensional disorder parameter of the former being mapped to the staggered magnetization order parameter of the latter. The model has a critical point with long-range correlations between edges, where a continuum random geometry can be defined, exactly as in Kazakov's famed 2D random lattice Ising model but now in any number of dimensions.
Dong, Yan; Lin, Chunyu; Zhao, Yao; Yao, Chao
2017-07-01
In texture-plus-depth format of three-dimensional visual data, both texture and depth maps are required to synthesize a desired view via depth-image-based rendering. However, the depth maps captured or estimated always exist with low resolution compared to their corresponding texture images. We introduce a joint edge-guided convolutional neural network that upsamples the resolution of a depth map on the premise of synthesized view quality. The network takes the low-resolution depth map as an input using a joint edge feature extracted from the depth map and the registered texture image as a reference, and then produces a high-resolution depth map. We further use local constraints that preserve smooth regions and sharp edges so as to improve the quality of the depth map and synthesized view. Finally, a global looping optimization is performed with virtual view quality as guidance in the recovery process. We train our model using pairs of depth maps and texture images and then make tests on other depth maps and video sequences. The experimental results demonstrate that our scheme outperforms existing methods both in the quality of the depth maps and synthesized views.
Calculating PageRank in a changing network with added or removed edges
Engström, Christopher; Silvestrov, Sergei
2017-01-01
PageRank was initially developed by S. Brinn and L. Page in 1998 to rank homepages on the Internet using the stationary distribution of a Markov chain created using the web graph. Due to the large size of the web graph and many other real world networks fast methods to calculate PageRank is needed and even if the original way of calculating PageRank using a Power iterations is rather fast, many other approaches have been made to improve the speed further. In this paper we will consider the problem of recalculating PageRank of a changing network where the PageRank of a previous version of the network is known. In particular we will consider the special case of adding or removing edges to a single vertex in the graph or graph component.
Video Compression Schemes Using Edge Feature on Wireless Video Sensor Networks
Phat Nguyen Huu
2012-01-01
Full Text Available This paper puts forward a low-complexity video compression algorithm that uses the edges of objects in the frames to estimate and compensate for motion. Based on the proposed algorithm, two schemes that balance energy consumption among nodes in a cluster on a wireless video sensor network (WVSN are proposed. In these schemes, we divide the compression process into several small processing components, which are then distributed to multiple nodes along a path from a source node to a cluster head in a cluster. We conduct extensive computational simulations to examine the truth of our method and find that the proposed schemes not only balance energy consumption of sensor nodes by sharing of the processing tasks but also improve the quality of decoding video by using edges of objects in the frames.
Recursive neural networks for processing graphs with labelled edges: theory and applications.
Bianchini, M; Maggini, M; Sarti, L; Scarselli, F
2005-10-01
In this paper, we introduce a new recursive neural network model able to process directed acyclic graphs with labelled edges. The model uses a state transition function which considers the edge labels and is independent both from the number and the order of the children of each node. The computational capabilities of the new recursive architecture are assessed. Moreover, in order to test the proposed architecture on a practical challenging application, the problem of object detection in images is also addressed. In fact, the localization of target objects is a preliminary step in any recognition system. The proposed technique is general and can be applied in different detection systems, since it does not exploit any a priori knowledge on the particular problem. Some experiments on face detection, carried out on scenes acquired by an indoor camera, are reported, showing very promising results.
Managing ISR sharing policies at the network edge using Controlled English
Parizas, Christos; Pizzocaro, Diego; Preece, Alun; Zerfos, Petros
2013-05-01
In domains such as emergency response and military operations the sharing of Intelligence, Surveillance and Reconnaissance (ISR) assets among different coalition partners is regulated through policies. Traditionally, poli cies are created at the center of a coalitions network by high-level decision makers and expressed in low-level policy languages (e.g. Common Information Model SPL) by technical personnel, which makes them difficult to be understood by non-technical users at the edge of the network. Moreover, policies must often be modified by negotiation among coalition partners, typically in rapid response to the changing operational situation. Com monly, the users who must cope first with situational changes are those on the edge, so it would be very effective if they were able to create and negotiate policies themselves. We investigate the use of Controlled English (CE) as a means to define a policy representation that is both human-friendly and machine processable. We show how a CE model can capture a variety of policy types, including those based on a traditional asset ownership model, and those defining team-based asset sharing across a coalition. The use of CE is intended to benefit coalition networks by bridging the gap between technical and non-technical users in terms of policy creation and negoti ation, while at the same time being directly processable by a policy-checking system without transformation to any other technical representation.
D'Souza, P
2016-03-01
Tighter national budgets and escalating drug prices continue to present challenges for pharmaceutical market access strategies and societal cost of care. As pharmaceutical companies and medical governmental advisory organizations enter tougher negotiations, hospital trusts and other dispensary firms face barriers to receiving the best medical treatment, and as a result patient access is limited. The 2016 HealthNetwork Communications' Pharma Pricing & Market Access Europe meeting brought together pharmaceutical, medical governmental advisory and stakeholders and market access/pricing consultants, to encourage discussions and negotiations into how to improve the drug pricing system and consequential market access strategies while achieving the respective reimbursement and affordability objectives. Copyright 2016 Prous Science, S.A.U. or its licensors. All rights reserved.
Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy
Shunfu Jin
2016-01-01
Full Text Available The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy. In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs and then propose an appropriate pricing policy for secondary user (SU packets. We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline. With the help of a Quasi-Birth-Death (QBD process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS via the Matrix-Geometric Solution method. We assess the average latency of SU packets and the energy saving ratio of system. According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO method to search the socially optimal arrival rate of SU packets. By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets. Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.
Spectral and energy efficiency analysis of uplink heterogeneous networks with small-cells on edge
Shakir, Muhammad Zeeshan
2014-12-01
This paper presents a tractable mathematical framework to analyze the spectral and energy efficiency of an operator initiated deployment of the small-cells (e.g., femtocells) where the small-cell base stations are deliberately positioned around the edge of the macrocell. The considered deployment facilitates the cell-edge mobile users in terms of their coverage, spectral, and energy efficiency and is referred to as cell-on-edge (COE) configuration. The reduction in energy consumption is achieved by considering fast power control where the mobile users transmit with adaptive power to compensate the path loss, shadowing and fading. In particular, we develop a moment generating function (MGF) based approach to derive analytical bounds on the area spectral efficiency and exact expressions for the energy efficiency of the mobile users in the considered COE configuration over generalized-K fading channels. Besides the COE configuration, the derived bounds are also shown to be useful in evaluating the performance of random small-cell deployments, e.g., uniformly distributed small-cells. Simulation results are presented to demonstrate the improvements in spectral and energy efficiency of the COE configuration with respect to macro-only networks and other unplanned deployment strategies. © 2014 Elsevier B.V. All rights reserved.
M.F. Sabahi
2013-12-01
Full Text Available In this paper, based on the game theory, an optimized resource management algorithm for cognitive radio networks has been presented. Considering the personal interests, each user selects its own desired utility function and competes for channel and power selection. This non-cooperative approach is controlled through an appropriate pricing method. We have shown that if the profit function in a cooperative potential game is used as the pricing function in a non-cooperative network, the game governing the non-cooperative network will also become potential and will thus converge to Nash equilibrium. If the network is designed based on the cooperation of the users, the existence of selfish users among them will make the network be unstable. Besides, it decreases resource utilization gain. Using the recommended pricing has been shown to equilibrate the network. In simulations, by studying parameters like sum-rate of network and its total interference, it is shown that the resource utilization will be improved. Simulation results show that the equilibrium points also enjoy some optimality criteria such as Pareto optimality.
A Study of Non-Neutral Networks with Usage-based Prices
Altman, E; Caron, S; Kesidis, G; Rojas-Mora, J; Wong, S
2010-01-01
Hahn and Wallsten wrote that network neutrality "usually means that broadband service providers charge consumers only once for Internet access, do not favor one content provider over another, and do not charge content providers for sending information over broadband lines to end users." In this paper we study the implications of non-neutral behaviors under a simple model of linear demand-response to usage-based prices. We take into account advertising revenues and consider both cooperative and non-cooperative scenarios. In particular, we model the impact of side-payments between service and content providers. We also consider the effect of service discrimination by access providers, as well as an extension of our model to non-monopolistic content providers.
A RBF neural network model with GARCH errors: Application to electricity price forecasting
Coelho, Leandro dos Santos [Industrial and Systems Engineering Graduate Program, PPGEPS, Pontifical Catholic University of Parana, Imaculada Conceicao, 1155, Zip code 80215-901, Curitiba, Parana (Brazil); Santos, Andre A.P. [Department of Statistics, Universidad Carlos III de Madrid, C/ Madrid, 126, 28903 Getafe, Madrid (Spain)
2011-01-15
In this article, we propose a nonlinear forecasting model based on radial basis function neural networks (RBF-NNs) with Gaussian activation functions and robust clustering algorithms to model the conditional mean and a parametric generalized autoregressive conditional heteroskedasticity (GARCH) specification to model the conditional volatility. Instead of calibrating the parameters of the RBF-NNs via numerical simulations, we propose an estimation procedure by which the number of basis functions, their corresponding widths and the parameters of the GARCH model are jointly estimated via maximum likelihood along with a genetic algorithm to maximize the likelihood function. We use this model to provide multi-step-ahead point and direction-of-change forecasts of the Spanish electricity pool prices. (author)
Performance Enhancement by Measuring Traffic at Edge Routers in a High Speed Networks
K.Venkateswara Rao,
2011-06-01
Full Text Available There is an enormous increase of traffic on the network due to usage of real-time multimedia applications, which became an indispensable part of Internet traffic in the present day world. These applications include voice over IP, streaming audio and video, Internet gaming and real-time video conferencing. Such applications are multimedia information, geographical pictures, social network applications and global sharing applications. In order to reduce this traffic, high quality of service is needed which would be possible by Adaptive mechanisms. Integrated service on the network flows offer a bounded delay packet delivery to support real time applications. To provide bounded delay service, networks must use admission control to regulate their load. It is very mandatory to allocate and manage resources for multimedia traffic and various concurrent applications flows with real-time performance, in order to provide reliable quality of service (QoS. In this paper, we develop an enhanced model and an algorithm for admission control of real-time flows; comparisons among various distinguish features of admission control algorithms. In our approach, admission decision is made for each flowat the edge routers, but it is scalable because per-flow states are not maintained and the admission algorithm is simple. In the proposed admission control scheme, an admissible bandwidth, which is defined as the maximum rate of a flow that can be accommodated additionally while satisfying the delay performance requirements for both existing and new flows, is calculated based on the available bandwidth measured by edge routers. The admissible bandwidth is a threshold for admission control, and thus, it is very important to accurately estimate the admissible bandwidth. The performance of the proposed algorithm is evaluated by taking a set of simulation experiments using bursty traffic flows and the results are found to be encouraging.
David A Rolls
Full Text Available We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR epidemic dynamics. The types of network models are exponential random graph models (ERGMs and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a "hidden population". In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure.
A Hybrid Neural Network and H-P Filter Model for Short-Term Vegetable Price Forecasting
Youzhu Li
2014-01-01
Full Text Available This paper is concerned with time series data for vegetable prices, which have a great impact on human’s life. An accurate forecasting method for prices and an early-warning system in the vegetable market are an urgent need in people’s daily lives. The time series price data contain both linear and nonlinear patterns. Therefore, neither a current linear forecasting nor a neural network can be adequate for modeling and predicting the time series data. The linear forecasting model cannot deal with nonlinear relationships, while the neural network model alone is not able to handle both linear and nonlinear patterns at the same time. The linear Hodrick-Prescott (H-P filter can extract the trend and cyclical components from time series data. We predict the linear and nonlinear patterns and then combine the two parts linearly to produce a forecast from the original data. This study proposes a structure of a hybrid neural network based on an H-P filter that learns the trend and seasonal patterns separately. The experiment uses vegetable prices data to evaluate the model. Comparisons with the autoregressive integrated moving average method and back propagation artificial neural network methods show that our method has higher accuracy than the others.
On the Quick Construction of the Edge-Balance Index Sets of a Classes of Nested Network Graph
Hongjuan Tian
2012-07-01
Full Text Available The research of Boolean index sets of graphs is one of the important graph theory in the graph theory. Boolean index sets of graphs are to use the vertex sets and the edge sets of graphs to study the characteristics of various graphs and their inherent characteristics through corresponding the mapping function to Z_2. Its theory can be applied to information engineering, communication networks, computer science, economic management, medicine, etc. The edge-balance index set is an important issue in Boolean index set. In this paper, we defined edge-friendly labeling of the graph, edge-balance index set of the graph and the graph C_(n^m × P_(m_n (n=4,m≥2. We completely determine the edge-balance index sets of the graph C_(4^m × P_(m_4 (m=0(mod3 and solve formula proof and graphic tectonic methods.
Behavioural Responses and Network Effects of Time-varying Road Pricing
Van Amelsfort, D.H.
2009-01-01
Road pricing is a policy measure under consideration by many goverments and road authorities. Although objectives may be different any road pricing measure will impact the behaviour of travellers and the flow of traffic. In this research we specifically looked at the effects of road pricing measures
Heping PAN; Imad HAIDAR; Siddhivinayak KULKARNI
2009-01-01
This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predic-tions of crude oil prices, short-term prediction with time horizons of 1-3 days posits an important problem that is quite different from what has been studied in the litera-ture. The problem of such short-term predicability is tackled through two aspects. The first is to examine the existence of linear or nonlinear dynamic processes in crude oil prices.This sub-problem is addressed with statistical analysis in-volving the Brock-Dechert-Scheinkman test for nonlinearity.The second aspect is to test the capability of artificial neu-ral networks (ANN) for modeling the implicit nonlinearity for prediction. Four experimental models are designed and tested with historical data: (1) using only the lagged returns of filtered crude oil prices as input to predict the returns of the next days; this is used as the benchmark, (2) using only the information set of filtered crude oil futures price as in-put, (3) combining the inputs from the benchmark and sec-ond models, and (4) combing the inputs from the benchmark model and the intermarket information. In order to filter out the noise in the original price data, the moving averages of prices are used for all the experiments. The results provided sufficient evidence to the predictability of crude oil prices using ANN with an out-of-sample hit rate of 80%, 70%, and 61% for each of the next three days' trends.
David, L.; Percebois, J
2002-09-01
The gas deregulation process implies crucial choices concerning access to transportation networks. These choices deal with the nature, the structure and the level of access fees. This paper proposes an evaluation of different systems implemented both in Europe and North America, in relation to normative pricing references. The rules according to which shippers can buy or sell capacity represent another kind of choice that Regulators have to make. This paper proposes a simple model which demonstrates that secondary market prices should not be subject to a cap and emphasizes the need of a 'use-it-or-lose-it' rule on this market. (authors)
Titus SUCIU
2013-01-01
In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...
Titus SUCIU
2013-01-01
In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...
Energy-Efficient Caching for Mobile Edge Computing in 5G Networks
Zhaohui Luo
2017-05-01
Full Text Available Mobile Edge Computing (MEC, which is considered a promising and emerging paradigm to provide caching capabilities in proximity to mobile devices in 5G networks, enables fast, popular content delivery of delay-sensitive applications at the backhaul capacity of limited mobile networks. Most existing studies focus on cache allocation, mechanism design and coding design for caching. However, grid power supply with fixed power uninterruptedly in support of a MEC server (MECS is costly and even infeasible, especially when the load changes dynamically over time. In this paper, we investigate the energy consumption of the MECS problem in cellular networks. Given the average download latency constraints, we take the MECS’s energy consumption, backhaul capacities and content popularity distributions into account and formulate a joint optimization framework to minimize the energy consumption of the system. As a complicated joint optimization problem, we apply a genetic algorithm to solve it. Simulation results show that the proposed solution can effectively determine the near-optimal caching placement to obtain better performance in terms of energy efficiency gains compared with conventional caching placement strategies. In particular, it is shown that the proposed scheme can significantly reduce the joint cost when backhaul capacity is low.
Low-Complexity One-Dimensional Edge Detection in Wireless Sensor Networks
Martalò Marco
2010-01-01
Full Text Available In various wireless sensor network applications, it is of interest to monitor the perimeter of an area of interest. For example, one may need to check if there is a leakage of a dangerous substance. In this paper, we model this as a problem of one-dimensional edge detection, that is, detection of a spatially nonconstant one-dimensional phenomenon, observed by sensors which communicate to an access point (AP through (possibly noisy communication links. Two possible quantization strategies are considered at the sensors: (i binary quantization and (ii absence of quantization. We first derive the minimum mean square error (MMSE detection algorithm at the AP. Then, we propose a simplified (suboptimum detection algorithm, with reduced computational complexity. Noisy communication links are modeled either as (i binary symmetric channels (BSCs or (ii channels with additive white Gaussian noise (AWGN.
R.P. Faber (Riemer)
2010-01-01
textabstractThis thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects of price setting. First, it studies whether the existence of a suggested price has a coordinating effect on the prices of firms. Second
Javier Sandoval
2011-12-01
Full Text Available A review of the representative models of machine learning research applied to the foreign exchange rate and stock price prediction problem is conducted. The article is organized as follows: The first section provides a context on the definitions and importance of foreign exchange rate and stock markets. The second section reviews machine learning models for financial prediction focusing on neural networks, SVM and evolutionary methods. Lastly, the third section draws some conclusions.
Fattahi, Mohammad; Govindan, Kannan
2017-01-01
with different quality levels are assumed dependent on offered acquisition prices to customer zones. A uniform distribution function defines the expected price of each customer zone for one unit of each used product. Using two-stage stochastic programming, a mixed-integer linear programming model is proposed...
Fluctuation of USA Gold Price - Revisited with Chaos-based Complex Network Method
Bhaduri, Susmita; Ghosh, Subhadeep
2016-01-01
We give emphasis on the use of chaos-based rigorous nonlinear technique called Visibility Graph Analysis, to study one economic time series - gold price of USA. This method can offer reliable results with fiinite data. This paper reports the result of such an analysis on the times series depicting the fluctuation of gold price of USA for the span of 25 years(1990 - 2013). This analysis reveals that a quantitative parameter from the theory can explain satisfactorily the real life nature of fluctuation of gold price of USA and hence building a strong database in terms of a quantitative parameter which can eventually be used for forecasting purpose.
Ahangar, Reza Gharoie; Pournaghshband, Hassan
2010-01-01
In this paper, researchers estimated the stock price of activated companies in Tehran (Iran) stock exchange. It is used Linear Regression and Artificial Neural Network methods and compared these two methods. In Artificial Neural Network, of General Regression Neural Network method (GRNN) for architecture is used. In this paper, first, researchers considered 10 macro economic variables and 30 financial variables and then they obtained seven final variables including 3 macro economic variables and 4 financial variables to estimate the stock price using Independent components Analysis (ICA). So, we presented an equation for two methods and compared their results which shown that artificial neural network method is more efficient than linear regression method.
Qi, Xingqin; Song, Huimin; Wu, Jianliang; Fuller, Edgar; Luo, Rong; Zhang, Cun-Quan
2017-09-01
Clustering algorithms for unsigned social networks which have only positive edges have been studied intensively. However, when a network has like/dislike, love/hate, respect/disrespect, or trust/distrust relationships, unsigned social networks with only positive edges are inadequate. Thus we model such kind of networks as signed networks which can have both negative and positive edges. Detecting the cluster structures of signed networks is much harder than for unsigned networks, because it not only requires that positive edges within clusters are as many as possible, but also requires that negative edges between clusters are as many as possible. Currently, we have few clustering algorithms for signed networks, and most of them requires the number of final clusters as an input while it is actually hard to predict beforehand. In this paper, we will propose a novel clustering algorithm called Eb &D for signed networks, where both the betweenness of edges and the density of subgraphs are used to detect cluster structures. A hierarchically nested system will be constructed to illustrate the inclusion relationships of clusters. To show the validity and efficiency of Eb &D, we test it on several classical social networks and also hundreds of synthetic data sets, and all obtain better results compared with other methods. The biggest advantage of Eb &D compared with other methods is that the number of clusters do not need to be known prior.
Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks
GholamReza Yousefi
2014-03-01
Full Text Available This paper focuses on day-ahead (DA retailing for fixed and Time-of-Use (TOU price taker customers and DA real time pricing for active customers who participate in short-term markets. Customers’ response to the offered hourly prices are modeled using an hourly acceptance function which includes decreasing linear probability density functions based on the hourly minimum and maximum retail prices allowed by market regulators. Furthermore, the retailer offers to its active customers to participate in the DA demand response program and voluntary reduce their real time consumption for offered incentives. Numerical studies represent the effect of implementing demand response programs on the total benefit of retailing.
Marketing Planning, Pricing strategies, and The Use of Online Social Networks for Marketing in A SME
Bruno, Andrea
2013-01-01
The objectives of this dissertation are threefold. The dissertation is firstly aimed at recommending a practically useful marketing plan for Betterlanguages, a Nottingham based SME operating in the language services market. The recommendations for the internal and external analysis of the company are based on the academic tools outlined in the literature review. Second, the dissertation aims at offering suggestions concerning pricing strategy for Betterlanguages, by exploring the pricing l...
Latif M.
2016-01-01
Full Text Available Forecasting crude oil prices is very difficult to do because it has nonlinear and nonstationary characteristics. This research proposes a crude oil prices forecasting using a combination of EEMD and neural network. EEMD was used to decompose the price of crude oil into several IMFs and one residue. Before the training and testing was processed using FNN, EEMD output is normalized to fulfill network activation function. Data pattern of neural network was determined based on the results of normalization. The Learning method of neural network was based on Polak-Ribiére Conjugate Gradient algorithm. The output of neural networks on each component IMFs and the residue was aggregated using Adaline. The last process is denormalization of the Adaline output. Output of denormalization is the end result of the crude oil price forecasting. After forecasting results has been known, it then compared with the results of several neural networks learning algorithm. The result shows that the proposed method has better forecasting ability. This is indicated by the error value which was smaller than other forecasting algorithms for crude oil price forecasting.
Modelling the locational determinants of house prices: neural network and value tree approaches
Kauko, Tom Johannes
2002-01-01
Tom Kauko's book comprises an analysis of the locational element in house prices. Locational features can increase or decrease the value of a house compared with a similar one elsewhere. So far, the problem of isolating this element has been well documented in the literatures on spatial housing mark
Jafarian, Matin; Scherpen, Jacquelien M.A.; Aiello, Marco
2016-01-01
We present a price-based approach to deal with the challenges of the electrical power distribution systems with renewable generations. In specific, we address the power loss minimization and voltage regulation taking into account the actual grid capacity. Analogously, the cost function is reformulat
Summary of Pricing Strategy for Suzhou Rail Transit Network%苏州轨道交通线网收费策略综述
周明保; 陈莹; 施毅; 张宁
2011-01-01
为最大程度地发挥轨道交通的社会和经济效益,系统研究轨道交通收费策略.阐述苏州轨道交通线网收费策略的研究思路,在收费原则和运营阶段划分的基础上,详细分析票制、票种、票价等具体收费方法,建立轨道交通线网收费策略的理论体系.就收费策略对城市交通的影响进行研究,以期指导和不断调整收费策略.%In order to bring social and economic benefits of rail transit into full play, systematic research on its pricing strategy is imperative. This paper elaborates the guiding thoughts of pricing strategy for Suzhou rail transit network, analyzes the detailed pricing methods such as fare collection pattern, ticket type, price, etc. in line with pricing principles and operation stages, and establishes the theoretical system of the pricing strategy for rail transit network. The influence of the pricing strategy on urban traffic is also analyzed in order to guide and adjust the strategy constantly.
Capitalization of BRT Network Expansions Effects into Prices of Non-expansion Areas
2009-01-01
A before and after hedonic model is used to determine the property value impacts on properties already served by the transit system caused by extensions to Bogota's bus rapid transit system. Asking prices of residential properties belonging to an intervention area (N = 1,407 before, 1,570 after) or a control area (N = 267 before, 732 after) and offered for sale between 2001 and 2006 are used to determine capitalization of the enhanced regional access provided by the extension. Properties offe...
A Branch-and-Price Approach to the Feeder Network Design Problem
Santini, Alberto; Plum, Christian Edinger Munk; Røpke, Stefan
2017-01-01
transit times. Realistic instances are generated from the LinerLib benchmark suite. The problem is solved with a branch-and-price algorithm, which can solve most instances to optimality within one hour. The results also provide insights on the cost structure and desirable features of optimal routes....... These insights were obtained by means of an analysis where scenarios are generated varying internal and external conditions, such as fuel costs and port demands....
Gurudeo Anand Tularam
2012-01-01
Full Text Available House price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multivariate Regression (MR and nonlinear models of Neural Network (NN and Adaptive Neuro-Fuzzy (ANFIS are developed and compared. The GIS methods are used to integrate the data for the study area (Bathurst, Australia. While it was expected that the nonlinear methods would be much better the analysis shows NN and ANFIS are only slightly better than MR suggesting questions about high R2 often found in the literature. While structural data and macro-finance variables may contribute to higher R2 performance comparison was the goal of this study and besides the Australian data lacked structural elements. The results show that MR model could be improved. Also, the land value and location explained at best about 45% of the sale price variation. The analysis of price forecasts (within the 10% range of the actual prediction on average revealed that the non-linear models performed slightly better (29% than the linear (26%. The inclusion of social data improves the MR prediction in most of the suburbs. The suburbs analysis shows the importance of socially based locations and also variance due to types of housing dominant. In general terms of R2, the NN model (0.45 performed only slightly better than ANFIS 0.39 and better than MR (0.37; but the linear MRsoc performed better (0.42. In suburb level, the NN model (7/15 performed better than ANFIS (3/15 but the linear MR (5/15 was better than ANFIS. The improved linear MR (6/15 performed nearly as well as the non-linear NN. Linear methods appear to just as precise as the the more time consuming non linear methods in most cases for accounting for the differences and variation. However, when a much more in depth analysis is
Internet resource pricing models
Xu, Ke; He, Huan
2013-01-01
This brief guides the reader through three basic Internet resource pricing models using an Internet cost analysis. Addressing the evolution of service types, it presents several corresponding mechanisms which can ensure pricing implementation and resource allocation. The authors discuss utility optimization of network pricing methods in economics and underline two classes of pricing methods including system optimization and entities' strategic optimization. The brief closes with two examples of the newly proposed pricing strategy helping to solve the profit distribution problem brought by P2P
Modestino James W
2004-01-01
Full Text Available Digital video delivered over wired-to-wireless networks is expected to suffer quality degradation from both packet loss and bit errors in the payload. In this paper, the quality degradation due to packet loss and bit errors in the payload are quantitatively evaluated and their effects are assessed. We propose the use of a concatenated forward error correction (FEC coding scheme employing Reed-Solomon (RS codes and rate-compatible punctured convolutional (RCPC codes to protect the video data from packet loss and bit errors, respectively. Furthermore, the performance of a joint source-channel coding (JSCC approach employing this concatenated FEC coding scheme for video transmission is studied. Finally, we describe an improved end-to-end architecture using an edge proxy in a mobile support station to implement differential error protection for the corresponding channel impairments expected on the two networks. Results indicate that with an appropriate JSCC approach and the use of an edge proxy, FEC-based error-control techniques together with passive error-recovery techniques can significantly improve the effective video throughput and lead to acceptable video delivery quality over time-varying heterogeneous wired-to-wireless IP networks.
Kubisch, János; Türei, Dénes; Földvári-Nagy, László; Dunai, Zsuzsanna A; Zsákai, Lilian; Varga, Máté; Vellai, Tibor; Csermely, Péter; Korcsmáros, Tamás
2013-08-01
Autophagy, a highly regulated self-degradation process of eukaryotic cells, is a context-dependent tumor-suppressing mechanism that can also promote tumor cell survival upon stress and treatment resistance. Because of this ambiguity, autophagy is considered as a double-edged sword in oncology, making anti-cancer therapeutic approaches highly challenging. In this review, we present how systems-level knowledge on autophagy regulation can help to develop new strategies and efficiently select novel anti-cancer drug targets. We focus on the protein interactors and transcriptional/post-transcriptional regulators of autophagy as the protein and regulatory networks significantly influence the activity of core autophagy proteins during tumor progression. We list several network resources to identify interactors and regulators of autophagy proteins. As in silico analysis of such networks often necessitates experimental validation, we briefly summarize tractable model organisms to examine the role of autophagy in cancer. We also discuss fluorescence techniques for high-throughput monitoring of autophagy in humans. Finally, the challenges of pharmacological modulation of autophagy are reviewed. We suggest network-based concepts to overcome these difficulties. We point out that a context-dependent modulation of autophagy would be favored in anti-cancer therapy, where autophagy is stimulated in normal cells, while inhibited only in stressed cancer cells. To achieve this goal, we introduce the concept of regulo-network drugs targeting specific transcription factors or miRNA families identified with network analysis. The effect of regulo-network drugs propagates indirectly through transcriptional or post-transcriptional regulation of autophagy proteins, and, as a multi-directional intervention tool, they can both activate and inhibit specific proteins in the same time. The future identification and validation of such regulo-network drug targets may serve as novel intervention
The Griffiths Phase on Hierarchical Modular Networks with Small-world Edges
Li, Shanshan
2016-01-01
The Griffiths phase has been proposed to induce a stretched critical regime that facilitates self organizing of brain networks for optimal function. This phase stems from the intrinsic structural heterogeneity of brain networks, such as the hierarchical modular structure. In this work, we extend this concept to modified hierarchical networks with small-world connections based on Hanoi networks [1]. Through extensive simulations, we identify the essential role played by the exponential distribution of the inter-moduli connectivity probability across hierarchies on the emergence of the Griffiths phase in this network. Additionally, the spectral analysis on the adjacency matrix of the relevant networks [2] shows that a localized principle eigenvector is not necessarily the fingerprint of the Griffiths phase.
A new prediction method at the edge of optical burst switching network
Zhicheng Sui; Qingji Zeng; Shilin Xiao
2005-01-01
To achieve lower assembly delay at optical burst switching edge node, this paper proposes an approach called current weight length prediction (CWLP) to improve existing estimate mechanism in burst assembly.is introduced to make a dynamic tradeoff between the current and past traffic under different offset time.Simulation results show that CWLP can achieve a significant improvement in terms of traffic estimation in various offset time and offered load.
Wu, Z. [Laboratoire Pierre Sue, CEA-CNRS CE Saclay, Gif-sur Yvette (France)]|[INFN, Laboratori Nazionali di Frascati, Rome (Italy); Romano, C. [Rome, Univ. `Roma Tre` (Italy). Dip di Scienze Geologiche]|[Univ. Bayreuth (Germany). Bayerishes Geoinstitut; Marcelli, A.; Cibin, G. [INFN, Laboratori Nazionali di Frascati, Rome (Italy); Mottana, A.; Della Ventura, G. [Rome, Univ. `Roma Tre` (Italy). Dip di Scienze Geologiche]|[INFN, Laboratori Nazionali di Frascati, Rome (Italy); Giuli, G. [Florence Univ. (Italy). Dip. Scienze Mineralogiche; Courtial, P.; Dinwell, D.B. [Univ. Bayreuth (Germany). Bayerishes Geoinstitut
1998-11-01
The structure of aluminosilicate melts/glasses plays a key role in Earth Sciences for the understanding of rock-forming igneous processes, as well as in the Materials Sciences for their technical applications. In particular, the alkaline earth aluminosilicate glasses are an extremely important group of materials, with a wide range of commercial application, as well as serving as analogue for natural basaltic melts. However, definition of their structure and properties is still controversial, and in particular the role and effect of Al has long been a subject of debate. The paper reports a series of experimental x-ray absorption near-edge structure (XANES) spectra at the Al K edge on a series of synthetic glasses of peralkaline composition in the CaO-Al{sub 2}O{sub 3}-SiO{sub 2} system, together with a general theoretical framework for data analysis based on an ab initio full multiple scattering (MS) theory. It`s proposed an Al/Si tetrahedral network model for aluminosilicate glasses based on distorted polyhedra, with varying both the T-O (T=Al or Si) bond lengths and the T-O-T angles, and with different Al/Si composition. This model achieves a significant agreement between experiments and simulations. in these glasses, experimental data and theoretical results concur to support a model in which Al is network-former with a comparatively well ordered local medium-range order (up to 5 A).
A possible edge effect in enhanced network. [solar K-line observations by multichannel spectrometer
Jones, H. P.; Brown, D. R.
1977-01-01
K-line observations of enhanced network taken with the NASA/SPO Multichannel Spectrometer on September 28, 1975, in support of OSO-8 are discussed. The data show a correlation between core brightness and asymmetry for spatial scans which cross enhanced network boundaries. The implications of this result concerning mass flow in and near supergranule boundaries are discussed.
A possible edge effect in enhanced network. [solar K-line observations by multichannel spectrometer
Jones, H. P.; Brown, D. R.
1977-01-01
K-line observations of enhanced network taken with the NASA/SPO Multichannel Spectrometer on September 28, 1975, in support of OSO-8 are discussed. The data show a correlation between core brightness and asymmetry for spatial scans which cross enhanced network boundaries. The implications of this result concerning mass flow in and near supergranule boundaries are discussed.
Fujiwara, Ikuko; Remmert, Kirsten; Piszczek, Grzegorz; Hammer, John A
2014-05-13
Although capping protein (CP) terminates actin filament elongation, it promotes Arp2/3-dependent actin network assembly and accelerates actin-based motility both in vitro and in vivo. In vitro, capping protein Arp2/3 myosin I linker (CARMIL) antagonizes CP by reducing its affinity for the barbed end and by uncapping CP-capped filaments, whereas the protein V-1/myotrophin sequesters CP in an inactive complex. Previous work showed that CARMIL can readily retrieve CP from the CP:V-1 complex, thereby converting inactive CP into a version with moderate affinity for the barbed end. Here we further clarify the mechanism of this exchange reaction, and we demonstrate that the CP:CARMIL complex created by complex exchange slows the rate of barbed-end elongation by rapidly associating with, and dissociating from, the barbed end. Importantly, the cellular concentrations of V-1 and CP determined here argue that most CP is sequestered by V-1 at steady state in vivo. Finally, we show that CARMIL is recruited to the plasma membrane and only at cell edges undergoing active protrusion. Assuming that CARMIL is active only at this location, our data argue that a large pool of freely diffusing, inactive CP (CP:V-1) feeds, via CARMIL-driven complex exchange, the formation of weak-capping complexes (CP:CARMIL) at the plasma membrane of protruding edges. In vivo, therefore, CARMIL should promote Arp2/3-dependent actin network assembly at the leading edge by promoting barbed-end capping there.
Pricing and distributed QoS control for elastic network traffic
J.L. van den Berg (Hans); M.R.H. Mandjes (Michel); R. Núñez Queija (Rudesindo (Sindo))
2006-01-01
textabstractWeb measurements have shown that TCP flow sizes vary over several orders of magnitude. If network resources are shared fairly, the performance of short TCP flows is seriously degraded by long flows. This motivates prioritization of short over long flows, leading to significant
Prices and Network Externalities in Two-Sided Markets: The Belgian Newspaper Industry
van Cayseele, P.; Vanormelingen, S.
2007-01-01
This paper discusses the newspaper industry in Belgium from a two-sided market perspective. The reader and advertizing market for printed media are closely interlinked with each other by bilateral network externalities. This requires a specific structural model to estimate demand parameters for both
Prices and network effects in two-sided markets: the Belgian newspaper industry
Van Cayseele, P.; Vanormelingen, S.
2009-01-01
This paper investigates the two-sided nature of the newspaper industry. We explicitly take into account cross network effects that exist between advertisers and newspaper readers. On one side, advertisers' demand for publicity space depends on the number of newspaper readers and their
Prices and network effects in two-sided markets: the Belgian newspaper industry
Van Cayseele, P.; Vanormelingen, S.
2009-01-01
This paper investigates the two-sided nature of the newspaper industry. We explicitly take into account cross network effects that exist between advertisers and newspaper readers. On one side, advertisers' demand for publicity space depends on the number of newspaper readers and their characteristic
Price Competition in Two-Sided Markets with Heterogeneous Consumers and Network Effects
Filistrucchi, L.; Klein, T.J.
2013-01-01
We model a two-sided market with heterogeneous customers and two heterogeneous network effects. In our model, customers on each market side care differently about both the number and the type of customers on the other side. Examples of two-sided markets are online platforms or daily newspapers. In t
Getting to the edge: protein dynamical networks as a new frontier in plant-microbe interactions.
Garbutt, Cassandra C; Bangalore, Purushotham V; Kannar, Pegah; Mukhtar, M S
2014-01-01
A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials, and biofuel production. A systems or "-omics" perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics is vital to expanding our knowledge of how the intercellular communication processes are executed. This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed "-omes" and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the "-omics" approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.
Getting to the Edge: Protein dynamical networks as a new frontier in plant-microbe interactions
Cassandra C Garbutt
2014-06-01
Full Text Available A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials and biofuel production. A systems or -omics perspective frames the next frontier in the search for enhanced knowledge of plant network biology. The functional understanding of network structure and dynamics s is vital to expanding our knowledge of how the intercellular communication processes are executed. . This review article will systematically discuss various levels of organization of systems biology beginning with the building blocks termed –omes and ending with complex transcriptional and protein-protein interaction networks. We will also highlight the prevailing computational modeling approaches of biological regulatory network dynamics. The latest developments in the -omics approach will be reviewed and discussed to underline and highlight novel technologies and research directions in plant network biology.
Mind the edge! The role of adjacency matrix degeneration in maximum entropy weighted network models
Sagarra, Oleguer; Díaz-Guilera, Albert
2015-01-01
Complex network null models based on entropy maximization are becoming a powerful tool to characterize and analyze data from real systems. However, it is not easy to extract good and unbiased information from these models: A proper understanding of the nature of the underlying events represented in them is crucial. In this paper we emphasize this fact stressing how an accurate counting of configurations compatible with given constraints is fundamental to build good null models for the case of networks with integer valued adjacency matrices constructed from aggregation of one or multiple layers. We show how different assumptions about the elements from which the networks are built give rise to distinctively different statistics, even when considering the same observables to match those of real data. We illustrate our findings by applying the formalism to three datasets using an open-source software package accompanying the present work and demonstrate how such differences are clearly seen when measuring networ...
Xavier Fageda; Juan Luis Jiménez; Jordi Perdiguero
2010-01-01
Competition in airline markets may be tough. In this context, network carriers have two alternative strategies to compete with low-cost carriers. First, they may establish a low-cost subsidiary. Second, they may try to reduce costs using the main brand. This paper examines a successful strategy of the first type implemented by Iberia in the Spanish domestic market. Our analysis of data and the estimation of a pricing equation show that Iberia has been able to charge lower prices than rivals w...
Tadahiro Taniguchi
2015-07-01
Full Text Available A linear function submission-based double auction (LFS-DA mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP. This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor.
Valued Ties Tell Fewer Lies, II: Why Not To Dichotomize Network Edges With Bounded Outdegrees
Thomas, Andrew C
2011-01-01
Various methods have been proposed for creating a binary version of a complex network with valued ties. Rather than the default method of choosing a single threshold value about which to dichotomize, we consider a method of choosing the highest k outbound arcs from each person and assigning a binary tie, as this has the advantage of minimizing the isolation of nodes that may otherwise be weakly connected. However, simulations and real data sets establish that this method is worse than the default thresholding method and should not be generally considered to deal with valued networks.
Huang, Yi; Tan, Jianbin; Wu, Bin
A novel method is proposed in this paper to find the promotive relationship of products from a network point of view. Firstly, a product network is built based on the dataset of handsets’ sale information collected from all outlets of a telecom operator of one province of China, with a period from Jan. 2006 to Jul. 2008. Then the edge enhanced model is applied on product network to divide all the products into several groups, according to which each outlet is assigned to class A or class B for a certain handset. Class A is defined as the outlet which sell the certain handset and contains all of handsets of its group, while other situation for class B which sell the certain handset too. It’s shown from the result of analysis on these two kinds of outlets that many handsets are sold better in outlets of class A than that of class B, even though the sales revenue of all these outlets in the time period is close. That is to say the handsets within a group would promote the sale for each other. Furthermore, a method proposed in this paper gives a way to find out the important attributes of the handsets which lead them to br divided into the same group, and it also explains how to add a new handset to an existing group and where would the new handset be sold best.
Bernard Y Tumbelaka
2014-01-01
Full Text Available Objectives: The aim of the present research was to identify pulpitis through periapical radiography by applying edges as basis image features, the texture description and the artificial neural networks (ANNs. Materials and Methods: Input image data records of 10 molar and 10 canine teeth were used. The clinical diagnosis of interest cases were represented as normal pulp, reversible and irreversible pulpitis, and necrotic pulp. The following image processing steps were done. First, the data records were converted digitally and preprocessed as its original image using the Gaussian Filter to obtain the best smoothed intensity distribution. Second, the local image differentiation was used to produce edge detector operators, e(x,y as the image gradient; ∇f(x,y providing useful information about the local intensity variations. Third, these results were analyzed by using the texture descriptors to obtain digitally the image entropy, H. The fourth step, all were characterized by the ANNs. Results: The edge detection carried important information about the object boundaries of pulpal health and pain conditions in the dental pulp significantly. The image entropy which was identified, the diagnostic term, was obtained from texture descriptors in the segmentation regions where the curves of pulp states tent convergence with the normal pulp line from 4.9014 to 4.6843 decreasing to the reversible and the irreversible pulpitis line include the nectrotic pulp line from 4.6812 to 4.5926 and then inputting to the ANNs analysis at the same of mean square error around 0.0003. Conclusions: Referred to these results, the correlation of the image entropy and the ANNs analysis could be linearly classified with the critical point of 4.6827. Finally, it could be concluded that the direct reading radiography is better to be digitized in order to provide us the best choice for diagnosis validation.
Design of network-coding based multi-edge type LDPC codes for multi-source relaying systems
Li, Jun; Malaney, Robert; Yuan, Jinhong
2009-01-01
In this paper we investigate a multi-source LDPC scheme for a Gaussian relay system, where M sources communicate with the destination under the help of a single relay (M-1-1 system). Since various distributed LDPC schemes in the cooperative single-source system, e.g. bilayer LDPC and bilayer multi-edge type LDPC (BMET-LDPC), have been designed to approach the Shannon limit, these schemes can be applied to the $M-1-1$ system by the relay serving each source in a round-robin fashion. However, such a direct application is not optimal due to the lack of potential joint processing gain. In this paper, we propose a network coded multi-edge type LDPC (NCMET-LDPC) scheme for the multi-source scenario. Through an EXIT analysis, we conclude that the NCMET-LDPC scheme achieves higher extrinsic mutual information, relative to a separate application of BMET-LDPC to each source. Our new NCMET-LDPC scheme thus achieves a higher threshold relative to existing schemes.
Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move
Grzegorczyk, Marco; Husmeier, Dirk
2008-01-01
Applications of Bayesian networks in systems biology are computationally demanding due to the large number of model parameters. Conventional MCMC schemes based on proposal moves in structure space tend to be too slow in mixing and convergence, and have recently been superseded by proposal moves in t
Transition from monopoly pricing to competitive pricing
Perera, L. [Eastern Energy Ltd., Melbourne, VIC (Australia)
1995-12-31
The Victorian Government has embarked on a program to restructure the State electricity supply industry, that will be the precursor to reform throughout the whole of Australia. The Government is depending on competition to drive efficiency improvements to both generation and distribution businesses. Retail pricing will be the key determinant to a future assessment of the success or failure of these reforms. The paper examines electricity pricing before and after the restructuring from the viewpoint of a practitioner at the cutting edge of the reform process. Economic rationale is put forward why the Value Proposition will replace the Cost Recovery basis previously used in electricity pricing. It is concluded that limitations of interstate links will temper intestate competition unless innovative solution can be found. The current method of setting market prices based on a `Pool System` is only efficient if the generators bid their marginal price on a regular basis. In essence the pool replaces the `merit order` previously used to load generators and is basically a scheduling mechanism. Serious consideration needs to be given to the question whether this mechanism should be also setting the price of electricity. (author). 5 tabs.
Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S
2015-09-01
The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods.
Getting to the Edge: Protein dynamical networks as a new frontier in plant-microbe interactions
Garbutt, Cassandra C.; Bangalore, Purushotham V.; Pegah eKannar; Shahid eMukhtar
2014-01-01
A systems perspective on diverse phenotypes, mechanisms of infection, and responses to environmental stresses can lead to considerable advances in agriculture and medicine. A significant promise of systems biology within plants is the development of disease-resistant crop varieties, which would maximize yield output for food, clothing, building materials, and biofuel production. A systems or “-omics” perspective frames the next frontier in the search for enhanced knowledge of plant network bi...
Salim Lahmiri
2014-07-01
Full Text Available This paper presents a forecasting model that integrates the discrete wavelet transform (DWT and backpropagation neural networks (BPNN for predicting financial time series. The presented model first uses the DWT to decompose the financial time series data. Then, the obtained approximation (low-frequency and detail (high-frequency components after decomposition of the original time series are used as input variables to forecast future stock prices. Indeed, while high-frequency components can capture discontinuities, ruptures and singularities in the original data, low-frequency components characterize the coarse structure of the data, to identify the long-term trends in the original data. As a result, high-frequency components act as a complementary part of low-frequency components. The model was applied to seven datasets. For all of the datasets, accuracy measures showed that the presented model outperforms a conventional model that uses only low-frequency components. In addition, the presented model outperforms both the well-known auto-regressive moving-average (ARMA model and the random walk (RW process.
A Novel Coordinated Edge Caching with Request Filtration in Radio Access Network
Yang Li
2013-01-01
Full Text Available Content caching at the base station of the Radio Access Network (RAN is a way to reduce backhaul transmission and improve the quality of experience. So it is crucial to manage such massive microcaches to store the contents in a coordinated manner, in order to increase the overall mobile network capacity to support more number of requests. We achieve this goal in this paper with a novel caching scheme, which reduces the repeating traffic by request filtration and asynchronous multicast in a RAN. Request filtration can make the best use of the limited bandwidth and in turn ensure the good performance of the coordinated caching. Moreover, the storage at the mobile devices is also considered to be used to further reduce the backhaul traffic and improve the users’ experience. In addition, we drive the optimal cache division in this paper with the aim of reducing the average latency user perceived. The simulation results show that the proposed scheme outperforms existing algorithms.
Nonlinear prediction of gold prices based on BP neural network%基于 BP神经网络的黄金价格非线性预测
张延利
2013-01-01
针对黄金价格的非线性特征和神经网络的自身特点，利用BP神经网络建立了黄金价格的非线性预测模型。实证研究结果表明，BP神经网络模型具有较好的预测精度，可以为黄金投资和宏观经济决策提供一定的参考依据。%According to the neural network nonlinear characteristics of gold price and its own characteristics ,using BP neural network nonlinear prediction model was set up for the price of gold .The results show that the BP prediction has good accuracy and is available to provide references for the gold investment and macroeconomic decisions .
Montri Inthachot
2016-01-01
Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.
Núñez Tabales, Julia M.
2013-01-01
Full Text Available Econometric models, in the estimation of real estate prices, are a useful and realistic approach for buyers and for local and fiscal authorities. From the classical hedonic models to more data driven procedures, based on Artificial Neural Networks (ANN, many papers have appeared in economic literature trying to compare the results attained with both approaches. We insist on the use of ANN, when there is enough statistical information, and will detail some comparisons to hedonic modeling, in a medium size city in the South of Spain, with an extensive set of data spanning over several years, collected before the actual downturn of the market. Exogenous variables include each dwelling's external and internal data (both numerical and qualitative, and data from the building in which it is located and its surroundings. Alternative models are estimated for several time intervals, and enabling the comparison of the effects of the rising prices during the bull market over the last decade. || Los modelos econométricos en la valoración de precios inmobiliarios constituyen una herramienta útil tanto para los compradores como para las autoridades locales y fiscales. Desde los modelos hedónicos clásicos hasta los planteamientos actuales a través de redes neuronales artificiales (RNA, han tenido lugar numerosas aportaciones en la literatura económica que tratan de comparar los resultados de ambos métodos. Insistimos en el empleo de RNA en el caso de disponer de suficiente información estadística. En este trabajo se aplica dicha metodología en una ciudad de tamaño medio situada en el sur de España, utilizando una extensa muestra de datos que comprende varios años precedentes a la crisis actual. Las variables utilizadas -tanto cuantitativas como cualitativas- incluyen datos externos e internos de la vivienda, del edificio en el que está localizada, así como de su entorno. Se construyen varios modelos alternativos para distintos intervalos de
Gabriele Lohmann
Full Text Available The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED. TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.
Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus
2016-01-01
The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.
Hedonic Housing Price Model Via BP Neural Network%Hedonic住宅特征价格模型的BP神经网络方法
司继文; 韩莹莹; 罗希
2012-01-01
In this paper, hedonic pricing model is used to assess the housing price in Washington, USA. For the pricing model, in this paper, the crime variables around the house are included. The model is built by hedonic pricing method through using traditional OLS method and neural network to simulate and with data modified by Box-cox transformation. The result shows the change in criminal rate makes the housing price change, and as the distance of crime to the housing and the types of crimes changes, the house price changes from -5. 78% to 2. 08%. In July of 2007 and the whole 2008, the influences of crime on housing price are different. It also shows that neural network is more accurate than the traditional OLS method with 5. 74% higher degree of approximation, and shows better features.%房地产在金融市场中占有举足轻重的地位,其价格变化对整个金融市场有着显著的影响.采用特征价格模型,对美国一线城市2007年6月及2008年的房价进行了相关定价研究.对传统特征价格模型的属性因子进行了扩充,加入房产周边犯罪率因子进行模拟；在数值方法计算方面,首先对数据进行了Box-cox变换,分别采用BP神经网络及传统的最小二乘法进行数值模拟分析,结果表明,房价随犯罪事件类型及发生距离房地产的远近有—5.78％～2.08％的变化；在2008年与2007年6月的不同时段内,犯罪率的变化对房价的影响有所不同.BP神经网络模拟的价格与实际交易价格曲线比传统最小二乘模拟的价格曲线精度高出5.74个百分点.
Zhilong Wang
2014-01-01
Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.
Armstrong, Mark
2008-01-01
This paper surveys recent economic research on price discrimination, both in monopoly and oligopoly markets. Topics include static and dynamic forms of price discrimination, and both final and input markets are considered. Potential antitrust aspects of price discrimination are highlighted throughout the paper. The paper argues that the informational requirements to make accurate policy are very great, and with most forms of price discrimination a laissez-faire policy may be the best availabl...
Nielsen, Søren Bo
2014-01-01
Against a background of rather mixed evidence about transfer pricing practices in multinational enterprises (MNEs) and varying attitudes on the part of tax authorities, this paper explores how multiple aims in transfer pricing can be pursued across four different transfer pricing regimes. A MNE h...
Network Externalities and Behavior-Based Price Discrimination%网络外部性与基于行为的区别定价
董亮; 任剑新
2012-01-01
近年来,基于行为的区别定价成为区别定价领域研究的热点,但是这方面的文献却鲜有涉及到市场中存在着网络外部性的情形。在理性预期的假设下,本文通过一个两阶段双寡头博弈模型分析了网络外部性与基于行为的区别定价对子博弈精炼纳什均衡的影响。在成熟市场上,网络外部性会对具有不同初始市场份额的厂商产生不同影响;在新兴市场上,无论厂商采取何种定价策略,网络外部性都会加剧市场上的竞争,导致厂商利润下降。与统一定价下的子博弈精炼纳什均衡相比,基于行为的区别定价会加剧竞争从而导致厂商利润的下降,但是会造成较多社会福利的无谓损失。%Behavior-based price discrimination has received much attention in the recent economic literatures, but the literatures of this topic rarely deal with status of market with network externalities. Under the assumption of rational expectation, this paper studies the effect of network externalities and behavior - based price discrimination to the subgame perfect Nash equilibrium by using a two - period duopoly model. In a mature market, network externalities would exert varying influences on different firms depending on their initial market share. In a new market,network externalities would increase competition and reduce firms＇ profits no matter what kind of pricing strategy the firms take. Compared with the SPE of uniform pricing, behavior - based price discrimination would increase competition and reduce firms＇ profits,but it also creates more dead -weight loss to the society.
银行卡网络交换费差别定价模型研究%Interchange Fee Discrimination Pricing Model of a Bankcard Network
孙毅坤; 胡祥培
2011-01-01
The pricing of card payments' service is a difficult and challenging issue to research, which is closely related to the stability and prosperity of card payments' market. In consideration of the fact that the interchange fee lies in the center of the pricing system of a bankcard network, which is normally used to adjust the benefits between the issuers and the acquirers. The interchange fee pricing principle was given first on the basis of the price discrimination theories, in which the statistical and mathematical methods were combined with the specific characteristics and the demand of card payments development. And then the interchange fee discrimination pricing model for the card consumption payments across different banks was constructed under the processes of optimizing the classification of the merchants, introducing the level-pricing method and adopting the two-part pricing way. By data analysis, a new merchants' classification method and dynamic adjustment mechanism based on the transactions characteristics, a specific level pricing method and detail two-part pricing standards were given finally. The research results indicate that this paper contributed by exploring the interchange fee discrimination method and submitting the relative optimal paths based on current situations, which is not only helpful for commercial banks and regulation departments to make pricing decisions or to make relative policies, but also useful to push the deeper research of the electronic payments and pricing theories further.%银行卡支付服务定价是金融领域富有挑战性的研究难题,它事关银行卡交易市场的稳定和繁荣.交换费是银行卡网络价格体系的核心,对发卡机构与收单机构的利益关系具有重要的调节作用.结合中国银行卡市场的特殊性以及发展需求,基于差别定价理论,采用数量分析方法,提出优化商户分类、引入层级定价与二部制定价相结合的交换费优化思路,建立基
Bisheng He
2014-01-01
Full Text Available A time-space network based optimization method is designed for high-speed rail train timetabling problem to improve the service level of the high-speed rail. The general time-space path cost is presented which considers both the train travel time and the high-speed rail operation requirements: (1 service frequency requirement; (2 stopping plan adjustment; and (3 priority of train types. Train timetabling problem based on time-space path aims to minimize the total general time-space path cost of all trains. An improved branch-and-price algorithm is applied to solve the large scale integer programming problem. When dealing with the algorithm, a rapid branching and node selection for branch-and-price tree and a heuristic train time-space path generation for column generation are adopted to speed up the algorithm computation time. The computational results of a set of experiments on China’s high-speed rail system are presented with the discussions about the model validation, the effectiveness of the general time-space path cost, and the improved branch-and-price algorithm.
Juan D Velásquez
2008-12-01
Full Text Available Una red neuronal autorregresiva es estimada para el precio mensual brasileño de corto plazo de la electricidad, la cual describe mejor la dinámica de los precios que un modelo lineal autorregresivo y que un perceptrón multicapa clásico que usan las mismas entradas y neuronas en la capa oculta. El modelo propuesto es especificado usando un procedimiento estadístico basado en el contraste del radio de verosimilitud. El modelo pasa una batería de pruebas de diagnóstico. El procedimiento de especificación propuesto permite seleccionar el número de unidades en la capa oculta y las entradas a la red neuronal, usando pruebas estadísticas que tienen en cuenta la cantidad de los datos y el ajuste del modelo a la serie de precios. La especificación del modelo final demuestra que el precio para el próximo mes es una función no lineal del precio actual, de la energía afluente actual y de la energía almacenada en el embalse equivalente en el mes actual y dos meses atrás.An autoregressive neural network model is estimated for the monthly Brazilian electricity spot price, which describes the prices dynamics better than a linear autoregressive model and a classical multilayer perceptron using the same input and neurons in the hidden layer. The proposed model is specified using a statistical procedure based on a likelihood ratio test. The model passes a battery of diagnostic tests. The proposed specification procedure allows us to select the number of units in hidden layer and the inputs to the neural network based on statistical tests, taking into account the number of data and the model fitting to the price time series. The final model specification demonstrates that the price for the next month is a nonlinear function of the current price, the current energy inflow, and the energy saved in the equivalent reservoir in the current month and two months ago.
Agrawal, A. V.; Kumar, R.; Venkatesan, S.; Zakhidov, A.; Zhu, Z.; Bao, Jiming; Kumar, Mahesh; Kumar, Mukesh
2017-08-01
The increased usage of hydrogen as a next generation clean fuel strongly demands the parallel development of room temperature and low power hydrogen sensors for their safety operation. In this work, we report strong evidence for preferential hydrogen adsorption at edge-sites in an edge oriented vertically aligned 3-D network of MoS2 flakes at room temperature. The vertically aligned edge-oriented MoS2 flakes were synthesised by a modified CVD process on a SiO2/Si substrate and confirmed by Scanning Electron Microscopy. Raman spectroscopy and PL spectroscopy reveal the signature of few-layer MoS2 flakes in the sample. The sensor's performance was tested from room temperature to 150 °C for 1% hydrogen concentration. The device shows a fast response of 14.3 s even at room temperature. The sensitivity of the device strongly depends on temperature and increases from ˜1% to ˜11% as temperature increases. A detail hydrogen sensing mechanism was proposed based on the preferential hydrogen adsorption at MoS2 edge sites. The proposed gas sensing mechanism was verified by depositing ˜2-3 nm of ZnO on top of the MoS2 flakes that partially passivated the edge sites. We found a decrease in the relative response of MoS2-ZnO hybrid structures. This study provides a strong experimental evidence for the role of MoS2 edge-sites in the fast hydrogen sensing and a step closer towards room temperature, low power (0.3 mW), hydrogen sensor development.
Internet Resource Pricing Models, Mechanisms, and Methods
He, Huan; Liu, Ying
2011-01-01
With the fast development of video and voice network applications, CDN (Content Distribution Networks) and P2P (Peer-to-Peer) content distribution technologies have gradually matured. How to effectively use Internet resources thus has attracted more and more attentions. For the study of resource pricing, a whole pricing strategy containing pricing models, mechanisms and methods covers all the related topics. We first introduce three basic Internet resource pricing models through an Internet cost analysis. Then, with the evolution of service types, we introduce several corresponding mechanisms which can ensure pricing implementation and resource allocation. On network resource pricing methods, we discuss the utility optimization in economics, and emphasize two classes of pricing methods (including system optimization and entities' strategic optimizations). Finally, we conclude the paper and forecast the research direction on pricing strategy which is applicable to novel service situation in the near future.
A Sublogarithmic Approximation for Highway and Tollbooth Pricing
Gamzu, Iftah
2010-01-01
An instance of the tollbooth problem consists of an undirected network and a collection of single-minded customers, each of which is interested in purchasing a fixed path subject to an individual budget constraint. The objective is to assign a per-unit price to each edge in a way that maximizes the collective revenue obtained from all customers. The revenue generated by any customer is equal to the overall price of the edges in her desired path, when this cost falls within her budget; otherwise, that customer will not purchase any edge. Our main result is a deterministic algorithm for the tollbooth problem on trees whose approximation ratio is O(log m / log log m), where m denotes the number of edges in the underlying graph. This finding improves on the currently best performance guarantees for trees, due to Elbassioni et al. (SAGT '09), as well as for paths (commonly known as the highway problem), due to Balcan and Blum (EC '06). An additional interesting consequence is a computational separation between tol...
Rohde, Carsten; Rossing, Christian Plesner
trade internally as the units have to decide what prices should be paid for such inter-unit transfers. One important challenge is to uncover the consequences that different transfer prices have on the willingness in the organizational units to coordinate activities and trade internally. At the same time...
Tenopir, Carol
1998-01-01
Presents results of a recent survey of over 100 public and academic libraries about pricing options from online companies. Most options fall into three categories: pay-as-you-go, fixed-rate, and user-based. Results are discussed separately for public and academic libraries and for consortial discounts. Trends in pricing options preferred by…
孙中桥; 陈菊红
2011-01-01
利用边界锁定技术对知识网进行研究.通过对跨组对织知识边界及形成机理的分析,得出知识网结构模型,在知识边界锁定的基础上,利用编码技术,初步研究跨组织知识网编码方法,从而为实现基于Internet的跨组织知识共享及协同工作准备了技术基础,同时也为大规模的科学知识研究层次化、权限化、模块化、集成化、信息化以及科学研究的一致性和动态更新及维护提供方法.%Knowledge network was studied by using edge locking technology in this paper. Through analyzing the knowl edge boundary and formation mechanism of the inter-organization, the paper obtained knowledge networks structure mod el. On the foundation of the knowledge edge locking, the knowledge network coding method of inter - organization was stud ied by using encoding technology. As a result, the technical bases of knowledge sharing and cooperation of inter - organiza tion were prepared to realize the E - knowledge networks. Meanwhile, a useful method for large - scale of ranklized, per missionlized, modularized, synchronized, informationalized scientific knowledge research was provided for consistency, dy namic update and maintenance of scientific research.
Pricing Strategies for CD-ROM Products.
Rowley, J. E.
1994-01-01
Pricing strategies for subscriptions and licenses for CD-ROMs are different for single users and networks. The basic components of pricing strategies are charges for subscription, connect line, display/print, telecommunication, session rate, special commands, and special services. Highlights selected supplier pricing strategies for single users…
2006-01-01
Please take note that after five years of stable prices at Restaurant No 1 a price increase will come into force on 1st January 2006. This increase has been agreed after discussions between the CSR (Comité de Surveillance des Restaurants) and the catering company Novae and will reflect the inflation rate of the last few years. In addition, a new children's menu will be introduced, as well as 'Max Havelaar' fair-trade coffee at a price of 1.70 CHF.
2005-01-01
Please take note that after five years of stable prices at Restaurant No 1 a price increase will come into force on 1st January 2006. This increase has been agreed after discussions between the CSR (Comité de Surveillance des Restaurants) and the catering company Novae and will reflect the inflation rate of the last few years. In addition, a new children's menu will be introduced as well as 'Max Havelaar' fair-trade coffee at a price of 1.70 CHF.
Study on Cascading Failures′Model of Edge in Coupled Networks%耦合网络边相继故障模型研究
王建伟; 蒋晨; 孙恩慧
2014-01-01
In order to deal with cascading failures in coupled networks, this study analyzes the dynamics mechanism of cascading failures and propose the cascading failures′model of edge in coupled networks.To improve the robustness of coupled networks a-gainst cascading failures, according to different measures, this study takes multiple perspectives to analyze the correlation be-tween the robustness of coupled networks with different link patterns and some parameters in our model.this study then discusses the influences of link patterns of coupled networks and the basic network model on cascading failures and states the whole protec-tion strategies in the proposed model.This study finds: the assortative link pattern can enhance the robustness of coupled net-works against cascading failures;the more similar the topological structures of two interdependent networks, the stronger the net-work robustness against cascading failures;the robustness of coupled networks has a positive correlation with the average degree;an appropriate increase in the number of symmetrical edges between two networks can improve the network robustness.Finally, the cascading failures′model of edge in the real coupled power grid is analyzed.%针对耦合网络上频发的相继故障问题，通过分析边级联故障蔓延的动力学演化机制，构建耦合网络上边相继故障模型。以提高耦合网络整体抵制相继故障能力为出发点，依据不同度量指标，多角度分析具有不同耦合模式的耦合网络鲁棒性与模型参数之间的关联性，研究耦合网络间耦合模式和网络基本模型等因素对相继故障的影响，探讨耦合网络边相继故障模型的整体保护策略。研究结果表明，同配连接模式能够增强耦合网络抵制级联故障的鲁棒性；相互依赖的两个耦合网络之间拓扑结构越相似，网络抵制相继故障的鲁棒性越强；耦合网络鲁棒性与网络平均度正相关；适当的增加
Electricity Price Forecasting Using Wavelet Neural Networks Optimized by GA%小波神经网络预测电价的新改进
涂启玉; 张茂林
2011-01-01
预测市场边际电价对于电力市场的参与者有十分重要的意义.该文首先分析了BP神经网络在电价预测方面的优劣势,然后基于小波分析,即用母小波取代Sigmoid函数建立了小波神经网络的电价预测模型,并用遗传算法优化神经网络的拓扑结构和各权重系数,从而避免BP神经网络的预测电价陷入局部极小值.实际计算表明,改进后的预测模型有效地提高了预测精度.%Forecasting the future electricity price is very important for every participators in the power market.This paper analyses the advantages and disadvantages of BP neural networks, then provides a wavelet-improved neural network model base on wavelet analysis and the topology structure and weight coefficient optimized by GA. Application to the real system shows that this model can improve the forecasting precision and avoid the limitation of the BP neural networks.
Fair pricing, and pricing paradoxes
Barbara Swart
2016-05-01
Full Text Available The St Petersburg Paradox revolves round the determination of a fair price for playing the St Petersburg Game. According to the original formulation, the price for the game is infinite, and, therefore, paradoxical. Although the St Petersburg Paradox can be seen as concerning merely a game, Paul Samuelson (1977 calls it a “fascinating chapter in the history of ideas”, a chapter that gave rise to a considerable number of papers over more than 200 years involving fields such as probability theory and economics. In a paper in this journal, Vivian (2013 undertook a numerical investigation of the St Petersburg Game. In this paper, the central issue of the paradox is identified as that of fair (risk-neutral pricing, which is fundamental in economics and finance and involves important concepts such as no arbitrage, discounting, and risk-neutral measures. The model for the St Petersburg Game as set out in this paper is new and analytical and resolves the so-called pricing paradox by applying a discounting procedure. In this framework, it is shown that there is in fact no infinite price paradox, and simple formulas for obtaining a finite price for the game are also provided.
A dual theory of price and value in a meso-scale economic model with stochastic profit rate
Greenblatt, R. E.
2014-12-01
The problem of commodity price determination in a market-based, capitalist economy has a long and contentious history. Neoclassical microeconomic theories are based typically on marginal utility assumptions, while classical macroeconomic theories tend to be value-based. In the current work, I study a simplified meso-scale model of a commodity capitalist economy. The production/exchange model is represented by a network whose nodes are firms, workers, capitalists, and markets, and whose directed edges represent physical or monetary flows. A pair of multivariate linear equations with stochastic input parameters represent physical (supply/demand) and monetary (income/expense) balance. The input parameters yield a non-degenerate profit rate distribution across firms. Labor time and price are found to be eigenvector solutions to the respective balance equations. A simple relation is derived relating the expected value of commodity price to commodity labor content. Results of Monte Carlo simulations are consistent with the stochastic price/labor content relation.
多媒体通信网络边缘实施策略研究%Research of Implementing Strategies of Edge of Multimedia Communication Networks
严碧惠
2011-01-01
多媒体通信网络具有连接通信主机、数位设备多和业务种类多等特点。因为IPv4地址面临枯竭，IPv6地址使用迫在眉捷。利用现有IPv4网络为承载网络，在边缘网络实现1Pv6化，是当前解决IPv4地址严重不足的一种解决方法。为了实现IPv4与IPv6的业务服务兼容，可以6t04和区分服务来解决两类地址转换引起的服务质量问题。%Multimedia communication networks are characterized with links of a lot of communication hosts or digital devices and support more class of business. IPv4 addresses are being used up, IPv6 addresses is imminent. It is a solution to the serious shortage of current IPv4 addresses that taking the existing network as the bearing network, to carry IPv6 on the edge network. In order to achieve compatibility of IPv4 to IPv6 business services, 6to4 and differentiated services are used to solve the QoS problem caused by translation of two types of address.
Marginal pricing of transmission services. An analysis of cost recovery
Perez-Arriaga, I.J.., Rubio, F.J. [Instituto de Investigacion Technologica, Universidad Pontificia Comillas, Madrid (Spain); Puerta, J.F.; Arceluz, J.; Marin, J. [Unidad de Planificacion Estrategica, Iberdrola, Madrid (Spain)
1996-12-31
The authors present an in-depth analysis of network revenues that are computed with marginal pricing, and investigate the reasons why marginal prices in actual power systems fail to recover total incurred network costs. The major causes of the failure are identified and illustrated with numerical examples. The paper analyzes the regulatory implications of marginal network pricing in the context of competitive electricity markets and provides suggestions for the meaningful allocation of network costs among users. 5 figs., 9 tabs., 8 refs.
Earon, Ofri
2013-01-01
the building. The research explores and develops the architectural characteristics of correlations between the resident, the singular unit, the building and the given location at the edge zone. It approaches the edge zone of the urban house as a platform for dynamic interactions between these behaviours....... The following text includes the first draft of the first two chapters: introduction and theory. The chapters are not written completely, and some parts are written only as headlines. These headlines and other comments are marked in red. The text is on working progress and far from being finished...
Earon, Ofri
2014-01-01
of the involved actors at the border. By doing so, the study underlines a forgotten, yet important, role of this edge zone – being a zone of commonality between the house and city, between indoors and outdoors, between the man at home and the man at the street. The city of Copenhagen promotes porous borders...... is a collection of material from the case study of an ongoing PhD study titled: LIVING EDGE - The Architectural and Urban Prospect of Domestic Borders. The paper includes a description of the problem analysis, research question, method, discussion and conclusion....
Anna Umbert
2010-01-01
Full Text Available This work presents and describes the real-time testbed for all-IP Beyond 3G (B3G heterogeneous wireless networks that has been developed in the framework of the European IST AROMA project. The main objective of the AROMA testbed is to provide a highly accurate and realistic framework where the performance of algorithms, policies, protocols, services, and applications for a complete heterogeneous wireless network can be fully assessed and evaluated before bringing them to a real system. The complexity of the interaction between all-IP B3G systems and user applications, while dealing with the Quality of Service (QoS concept, motivates the development of this kind of emulation platform where different solutions can be tested in realistic conditions that could not be achieved by means of simple offline simulations. This work provides an in-depth description of the AROMA testbed, emphasizing many interesting implementation details and lessons learned during the development of the tool that may result helpful to other researchers and system engineers in the development of similar emulation platforms. Several case studies are also presented in order to illustrate the full potential and capabilities of the presented emulation platform.
盛天翔; 刘春林
2011-01-01
随着中国电子商务市场的迅速发展,传统渠道与网络渠道之间的竞争日趋激烈,国内外学者对两种渠道之间的价格竞争进行了广泛研究.构建包含一个传统企业和一个网络企业的双寡头城市线性Hotelling模型,定量分析各个影响因素对两渠道价格竞争的影响,通过多元线性回归模型进行计量检验.研究结果表明,电子商务成熟度越高,网络渠道和传统渠道的销售价格都会降低,但是传统渠道的价格降低速度要大于网络渠道;网上购物成本越高,网络渠道的价格越倾向于低于传统渠道.最后通过实际数据检验证实了这一结论,该结论对分析中国两种渠道的价格竞争情况具有指导作用.%The competition between traditional channel and network channel is becoming more and more severe with the rapid development of electronic business market in China.Scholars all over the world do a great deal of research on the price competition between these two channels.In this paper, we set up a city linear hotelling model.The study analyzed all factors which influence prices for both traditional and network channels by using quantitative method.In addition, we carried out some statistical test by using a multiple linear regression model.The results show that as electronic business gets more mature, prices in both network channel and traditional channel will get lower, but prices decrease in traditional channel will be bigger than that in network channel.Moreover, as cost for purchasing via network channels increases, price in network channel tends to be lower than that in traditional channel.Finally, we confirm this conclusion by carrying out some statistical test.This conclusion can as well be used to analyze the competition between traditional channels and network channels in China.
Pricing Mechanism in Power Market Construction
无
2005-01-01
The reform on electricity pricing mechanism is a critical problem in power market construction in China, and is in mutual supplementation and promotion with the latter. In particular, the pricing mechanism for electricity fed into network and that for electricity transmission and distribution as well as the relationship between coal and electricity prices, etc. Have to be studied in depth. This paper presents several solutions and suggestions to these problems.
Hong-Cheng Huang; Jie Zhang; Zu-Fan Zhang; Zhong-Yang Xiong
2016-01-01
Device-to-device (D2D) communication is an emerging technology for improving cellular networks, which plays an important role in realizing Internet of Things (IoT). The spectrum efficiency, energy efficiency and throughput of network can be enhanced by the cooperation among multiple D2D users in a self-organized method. In order to limit the interference of D2D users and load off the energy consumption of D2D users without decreasing communication quality, an interference-limited multi-user cooperation scheme is proposed for multiple D2D users to solve the energy problem and the interference problem in this paper. Multiple D2D users use non-orthogonal spectrums to form clusters by self-organized method. Multiple D2D users are divided into different cooperative units. There is no interference among different cooperative units so as to limit the interference of each D2D user in cooperative units. When the link capacity cannot meet the requirements of the user rate, it will produce an interrupt event. In order to evaluate the communication quality, the outrage probability of D2D link is derived by considering link delay threshold, data rate and interference. Besides the energy availability and signal-to-noise ratio (SNR) of each D2D user, the distance between D2D users is considered when selecting the relaying D2D users so as to enhance the signal-to-interference-plus-noise ratio (SINR) of D2D receiving users. Combining the derived outrage probability, the relationships among the average link delay threshold, the efficiency of energy and the efficiency of capacity are studied. The simulation results show that the interference-limited multiple D2D users cooperation scheme can not only help to oﬄoad energy consumption and limit the interference of D2D users, but also enhance the efficiency of energy and the efficiency of capacity.
Influence of Dynamical Change of Edges on Clustering Coefficients
Yuhong Ruan
2015-01-01
Full Text Available Clustering coefficient is a very important measurement in complex networks, and it describes the average ratio between the actual existent edges and probable existent edges in the neighbor of one vertex in a complex network. Besides, in a complex networks, the dynamic change of edges can trigger directly the evolution of network and further affect the clustering coefficients. As a result, in this paper, we investigate the effects of the dynamic change of edge on the clustering coefficients. It is illustrated that the increase and decrease of the clustering coefficient can be effectively controlled by adding or deleting several edges of the network in the evolution of complex networks.
基于时间序列的小波神经网络蔬菜价格预测模型%Vegetable Prices Prediction Model Based on Time-Series Wavelet Neural Network
钱彬彬; 谢申汝; 杨宝华
2016-01-01
Aiming at an accurate prediction of vegetable price, the cabbage monthly price data and the relevant factors data in Hefei Zhou Gudui farm product market from 2005 to 2014 were collected as samples. By analyzing principal component and using the Wavelet Neural Network intelligent analysis method, the price forecasting model was built and was compared with BP neural network model. The results show that the wavelet neural network predictive model has higher precision and better stability than the BP neural network. The establishment of the model would provide technical support for stability of the price and references for related policies.%为准确预测蔬菜价格变化规律，现以合肥市周谷堆农产品批发市场2005年~2014年白菜月度市场价格及相关影响因素数据为样本，通过主成分分析，利用小波神经网络智能分析方法，构建基于小波神经网络的价格预测模型，并与BP神经网络模型比较。结果表明，小波神经网络预测模型的预测精度比BP神经网络更高，且更加的稳定。该模型的构建对蔬菜价格的稳定、农业管理部门的决策支持具有重要的理论研究意义和实际价值。
李玉宝
2014-01-01
Bilateral market theory is the latest hot spot and frontier theory in the field of industrial organization in recent years. Social networking site has the typical characteristics of the bilateral market and its pricing and profit model has been the focus of platform enterprise. The paper built a monopoly platform-based pricing model, and analyzed the pricing model of social networking media platforms and software platform. The results showed that in social networking sites media platforms, the pricing of platform companies to advertisers is always higher than the cost of services they provide; in social networking site software platform, the platform companies may appear the situation of providing subsidies to the both sides of users.%院双边市场理论是近年来产业组织领域研究的最新热点和前沿理论。社交网站行业具有典型的双边市场特征，平台的定价和盈利模式一直是平台企业关注的焦点。本文构建基于垄断平台的定价模型，分析社交网站媒体平台和软件平台的定价模式。结果显示，在社交网站媒体平台，平台企业向广告商定价总是高于其提供的服务成本；在社交网站软件平台，平台企业可能出现同时向两边用户进行补贴的情况。
曲富丽
2015-01-01
The consumer price index has chaotic changes rules,the traditional models are difficult to accurately mining the change tendency,in order to obtain more ideal prediction results of consumer price index,a consumer price index prediction model by using chaos theory and improved neural network is put forward in this paper.Firstly,the phase space reconstruction is used to find the changes rules of consumer price index data,and then neural network is used to establish the prediction model of consumer price index which particle swarm optimization algorithm is used to select parameters of neural network,lastly,some consumer price index data are used to tested the performance.The experimental results show that,the proposed model can accurately reflect the changes of consumer price index,and the prediction results are conducive to macroeconomic analysis and decision making.%提出一种混沌理论和改进神经网络相融合的居民消费价格指数预测模型(Chaotic-NN)。首先对居民消费价格指数历史样本进行相空间重构,从中发现居民消费价格指数的变化信息,然后采用神经网络建立居民消费价格指数预测模型,并采用粒子群算法优化神经网络参数,最后利用多个居民消费价格指数预测实例对其性能进行验证性测试。结果表明,Chaotic-NN 可以全面描述居民消费价格指数变化的非线性和混沌性,拟合度和预测精度都比较高,真实地反映了居民消费价格指数的变化规律。
刘兰菊
2013-01-01
Distribution service pricing is one of important issues in the process of transmission and distribution separation. Traditional power distribution regulation is change to the incentive regulation. Based on the analysis of the related issues of distribution service pricing under scale competition mechanism, an incremental cost pricing model is proposed. The incremental cost can be estimated from the distribution network expansion program. The formulation of the distribution service pricing can be derived from the share of each user to distribution network load. The result of case study shows that the pricing model is effective for promoting competition among distribution companies, encouraging the parties to improve efficiency and reduce costs.%配电服务定价是输配分开过程中的重要问题之一,鉴于传统的配电管制正在向激励性管制转变,分析了标尺竞争机制下配电服务定价的相关问题,提出了一种基于标尺竞争机制的配电网增量成本定价模型,该模型基于配电网扩容计划估算增量成本和边际成本,并从每个配网使用者对配网负荷的使用份额来分析推导出配电服务价格.算例分析结果表明,该定价模型能有效促进配电公司之间的竞争,从而激励配电企业采取措施提高效率、降低成本.
Fernando Villada
2012-01-01
Full Text Available Este trabajo propone un modelo basado en redes neuronales artificiales para el pronóstico de los precios de dos de las principales acciones transadas en mercado de valores colombiano. El modelo propuesto se aplica al estudio de las acciones de Ecopetrol y Preferencial Bancolombia, empresas que negocian en las bolsas de valores de Colombia y Nueva York. Se utilizan dos estructuras de redes incluyendo como entradas la serie de precios diarios en la primera y la serie de precios más el índice del dólar estadounidense DXY en la segunda. Se prueban diferentes configuraciones de redes neuronales utilizando una serie de seis meses, donde los datos de los primeros cinco se utilizan para entrenamiento dejando el último mes para verificar la capacidad predictiva de la red. Los resultados muestran un buen comportamiento de las redes neuronales con bajos errores en su desempeño tanto en aprendizaje como en predicción.An artificial neural network model to forecast the price of two of the main shares traded in the Colombian stock exchange is proposed in this work. The model is applied to study the shares of Ecopetrol and Preferencial Bancolombia, companies that trade in the stock exchanges of Colombia and New York. Two network structures including the daily price series in the first and the price series plus the dollar index DXY in the latter are used. Different neural networks configurations are trained using a series of six months, where five months are used as training patterns and the next month is left to test the predictive capabilities of the network. The results show good performance of the neural networks with low training and testing errors.
Fidalgo-Marijuan, Arkaitz; Barandika, Gotzone; Bazán, Begoña; Urtiaga, Miren Karmele; Lezama, Luis; Arriortua, María Isabel
2013-07-15
Compound ([FeTPPbipy](•))n (TPP = meso-tetraphenylporphyrin and bipy = 4,4'-bipyridine) is the first example of a Fe-TPP-bipy coordination network, and it consists of 1D polymers packed through face-to-face and edge-to-face π-π interactions. The compound has been investigated by means of X-ray diffraction, IR, Mössbauer, UV-visible, and EPR spectroscopies, thermogravimetry, magnetic susceptibility measurements, and quantum-mechanical density functional theory (DFT) and time-dependent DFT calculations. The chemical formula for this compound can be confusing because it is compatible with Fe(II) and TPP(2-) anions. However, the spectroscopic and magnetic properties of this compound are consistent with the presence of low-spin Fe(III) ions and [FeTPPbipy](•) neutral radicals. These radicals are proposed to be formed by the reduction of metalloporphyrin, and the quantum-mechanical calculations are consistent with the fact that the acquired electrons are located on the phenyl groups of TPP.
Rodrigues, Alcantaro Lemes; Grimoni, Jose Aquiles Baesso [Univesidade de Sao Paulo (USP), SP (Brazil). Inst. de Eletrotecnica e Energia], emails: alcantaro@iee.usp.br, aquiles@iee.usp.br
2010-07-01
The commercialization of electricity in Brazil as well as in the world has undergone several changes over the past 20 years. In order to achieve an economic balance between supply and demand of the good called electricity, stakeholders in this market follow both rules set by society (government, companies and consumers) and set by the laws of nature (hydrology). To deal with such complex issues, various studies have been conducted in the area of computational heuristics. This work aims to develop a software to forecast spot market prices in using artificial neural networks (ANN). ANNs are widely used in various applications especially in computational heuristics, where non-linear systems have computational challenges difficult to overcome because of the effect named 'curse of dimensionality'. This effect is due to the fact that the current computational power is not enough to handle problems with such a high combination of variables. The challenge of forecasting prices depends on factors such as: (a) foresee the demand evolution (electric load); (b) the forecast of supply (reservoirs, hydrology and climate), capacity factor; and (c) the balance of the economy (pricing, auctions, foreign markets influence, economic policy, government budget and government policy). These factors are considered be used in the forecasting model for spot market prices and the results of its effectiveness are tested and huge presented. (author)
无
2011-01-01
The Chinese Government faces the task of stabilizing vegetable prices to avoid steep increases and dips Fluctuations of vegetable prices in China have recently caused near panic in the domestic market.Purchase prices for farm produce are decreasing dramatically
基于回声状态网络的电力市场电价预测%Echo-state-network based electricity price forecasting in electric power market
任远
2016-01-01
Traditional neural network based electricity price forecasting algorithm fails to meet current demands by future electric power market, with low accuracy and long computation time when the electric power price changes greatly. Using the method based on Echo-State-Network (ESN), an electricity power price short-term forecasting approach is proposed. Firstly, the principle of ESN is introduced and discussed. On this basis, the electricity power price short-term forecasting approach is proposed, including parameter selection, sampling data pre-processing and ESN training and forecast process. Then, the short-term electricity price forecasting is performed by ESN and BP neural network. The simulation results show that using ESN the short-term electricity price can be forecasted more quickly and steadily.%传统的神经网络算法在电价变化剧烈的情况下，精度较低并且所耗费的时间较长，难以满足电力市场发展的需求。为解决该问题，提出了一种基于回声状态网络(ESN)的短期电价预测方法。所提方法介绍了基于回声状态网络的预测原理，提出了电力市场短期电价的预测机制，包括参数选取、采样数据预处理和 ESN 训练及预测过程；并分别采用回声状态网络和反向传播算法(BP)神经网络进行短期电价预测。经过仿真验证，所提出的基于回声状态网络的电价预测具有较好的准确率和可行性。
1985-09-01
PROJECT. T ASK0 Artificial Inteligence Laboratory AREA It WORK UNIT NUMBERS V 545 Technology Square ( Cambridge, HA 02139 I I* CONTOOL1LIN@4OFFICE NAME...ARD-A1t62 62 EDGE DETECTION(U) NASSACNUSETTS INST OF TECH CAMBRIDGE 1/1 ARTIFICIAL INTELLIGENCE LAB E C HILDRETH SEP 85 AI-M-8 N99SI4-8S-C-6595...used to carry out this analysis. cce~iO a N) ’.~" D LI’BL. P p ------------ Sj. t i MASSACHUSETTS INSTITUTE OF TECHNOLOGY i ARTIFICIAL INTELLIGENCE
Ko, Jung Woo; Min, Kil Sik; Suh, Myunghyun Paik
2002-04-22
A 2-D metal-organic open framework having 1-D channels, [Cu(C(10)H(26)N(6))](3)[C(6)H(3)(COO)(3)](2).18H(2)O (1), was constructed by the self-assembly of the Cu(II) complex of hexaazamacrocycle A (A = C(10)H(26)N(6)) with sodium 1,3,5-benzenetricarboxylate (BTC(3)(-)) in DMSO-H(2)O solution. 1 crystallizes in the trigonal space group P with a = b = 17.705(1) A, c = 6.940(1) A, alpha = beta = 90 degrees, gamma = 120 degrees, V = 1884.0(3) A(3), Z = 1, and rho(calcd) = 1.428 g cm(-3). The X-ray crystal structure of 1 indicates that each Cu(II) macrocyclic unit binds two BTC(3-) ions in a trans position and each BTC(3-) ion coordinates three Cu(II) macrocyclic complexes to form 2-D coordination polymer layers with honeycomb cavities (effective size 8.1 A), and the layers are packed to generate 1-D channels perpendicularly to the 2-D layers. Solid 1 binds guest molecules such as MeOH, EtOH, and PhOH with different binding constant and capacity. By the treatment of 1 with aqueous solution of phenol, a hybrid solid [Cu(C(10)H(26)N(6))](3)[C(6)H(3)(COO)(3)](2).9PhOH.6H(2)O (2) was assembled. 2 crystallizes in the trigonal R3 space group with a = b = 20.461(1) A, c = 24.159(1) A, alpha = beta = 90 degrees, gamma = 120 degrees, V = 8759.2(7) A(3), Z = 3, and rho(calcd) = 1.280 g cm(-3). In 2, highly ordered 2-D noncovalent phenol layers are formed by the edge-to-face pi-pi interactions between the phenol molecules and are alternately packed with the coordination polymer layers in the crystal lattice.
7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing... advanced pricing factors. Class prices per hundredweight of milk containing 3.5 percent butterfat, component prices, and advanced pricing factors shall be as follows. The prices and pricing factors...
Kaiser, Ulrich; Mendez, Susan J.; Rønde, Thomas
2015-01-01
Reference price systems for prescription drugs have found widespread use as cost containment tools. Under such regulatory regimes, patients co-pay a fraction of the difference between pharmacy retail price of the drug and a reference price. Reference prices are either externally (based on drug...... prices in other countries) or internally (based on domestic drug prices) determined. In a recent study, we analysed the effects of a change from external to internal reference pricing in Denmark in 2005, finding that the reform led to substantial reductions in prices, producer revenues, and expenditures...
Huck, Steffen; Ruchala, Gabriele K.; Tyran, Jean-Robert
We experimentally examine the effects of flexible and fixed prices in markets for experience goods in which demand is driven by trust. With flexible prices, we observe low prices and high quality in competitive (oligopolistic) markets, and high prices coupled with low quality in non-competitive...... (monopolistic) markets. We then introduce a regulated intermediate price above the oligopoly price and below the monopoly price. The effect in monopolies is more or less in line with standard intuition. As price falls volume increases and so does quality, such that overall efficiency is raised by 50%. However...
张喜红
2016-01-01
研究运用LVQ神经网络进行脑部CT图像边缘检测的方法，以提高边缘检测的准确度。使用传统的Sobel算法对脑部CT图像进行边缘检测，作为网络学习的教师信号，并将脑部CT图像的中值特征量、方向性信息特征量、Krisch算子方向特征量3项特征量作为LVQ神经网络的输入信号，进行网络训练后，再将训练好的网络进行边缘检测。在Matlab 2010平台下进行仿真对比，结果显示改进算法边缘检测结果与实际相符，比传统Sobel算法更具优越性。%An edge detection method for brain CT scan images using LVQ neural network is studied to enhance the accuracy of edge detection.First, the traditional Sobel algorithm is used to detect the edge of brain CT scan images as the teacher′s signal for network learning.Second,the value of the median,the direc-tion of information characteristics,the direction of the characteristics of the Krisch operator of brain CT scan images are adopted as the input signal of the LVQ neural network to conduct network training.Finally,the trained neural network is used for edge detection.Comparison of computer simulations on Matlab 2010 shows that the improved method can achieve a credible result and has a better detection effect than the traditional Sobel algorithm.
Space-time modeling of electricity spot prices
Abate, Girum Dagnachew; Haldrup, Niels
In this paper we derive a space-time model for electricity spot prices. A general spatial Durbin model that incorporates the temporal as well as spatial lags of spot prices is presented. Joint modeling of space-time effects is necessarily important when prices and loads are determined in a network...
ACCOUNTING ASPECTS OF PRICING AND TRANSFER PRICING
TÜNDE VERES
2011-01-01
Full Text Available The pricing methods in practice need really complex view of the business situation and depend on the strategy and market position of a company. The structure of a price seems simple: cost plus margin. Both categories are special area in the management accounting. Information about the product costs, the allocation methodologies in cost accounting, the analyzing of revenue and different level of the margin needs information from accounting system. This paper analyzes the pricing methods from management accounting aspects to show out the role of the accounting system in the short term and long term pricing and transfer pricing decisions.
Image Edge Detection Based on Oscillation
FAN Hong; WANG Zhi-jie
2005-01-01
A new method for image edge detection based on a pulse neural network is proposed in this paper. The network is locally connected. The external input of each neuron of the network is gray value of the corresponding pixel. The synchrony of the neuron and its neighbors is detected by detection neurons. The edge of the image can be read off at minima of the total activity of the detection neurons.
Juniper, S. Kim; Sastri, Akash; Mihaly, Steven; Duke, Patrick; Else, Brent; Thomas, Helmuth; Miller, Lisa
2017-04-01
Marine pCO2 sensor technology has progressed to the point where months-long time series from remotely-deployed pCO2 sensors can be used to document seasonal and higher frequency variability in pCO2 and its relationship to oceanographic processes. Ocean Networks Canada recently deployed pCO2 sensors on two cabled platforms: a bottom-moored (400 m depth), vertical profiler at the edge of the northeast Pacific continental shelf off Vancouver Island, Canada, and a subtidal seafloor platform in the Canadian High Arctic (69˚ N) at Cambridge Bay, Nunavut. Both platforms streamed continuous data to a shore-based archive from Pro-Oceanus pCO2 sensors and other oceanographic instruments. The vertical profiler time series revealed substantial intrusions of corrosive (high CO2/low O2), saltier, colder water masses during the summertime upwelling season and during winter-time reversals of along-slope currents. Step-wise profiles during the downcast provided the most reliable pCO2 data, permitting the sensor to equilibrate to the broad range of pCO2 concentrations encountered over the 400 metre depth interval. The Arctic pCO2 sensor was deployed in August 2015. Reversing seasonal trends in pCO2 and dissolved oxygen values can be related to the changing balance of photosynthesis and respiration under sea ice, as influenced by irradiance. Correlation of pCO2 and dissolved oxygen sensor data and the collection of calibration samples have permitted evaluation of sensor performance in relation to operational conditions encountered in vertical profiling and lengthy exposure to subzero seawater.
Jäkel, Ina Charlotte; Sørensen, Allan
-cut prediction on the sign of the exporter price premium. However, the model unambiguously predicts a negative exporter price premium in terms of quality-adjusted prices, i.e. prices per unit of quality. This prediction is broadly borne out in the Danish data: while the magnitude of the premium varies across...
Huck, Steffen; Ruchala, Gabriele K.; Tyran, Jean-Robert
We experimentally examine the effects of flexible and fixed prices in markets for experience goods in which demand is driven by trust. With flexible prices, we observe low prices and high quality in competitive (oligopolistic) markets, and high prices coupled with low quality in non...
韩建辉
2015-01-01
电子商务企业的价格大战引起了业内的广泛关注，对电子商务企业的网络营销绩效有着重要的影响。本文在分析电商企业价格大战起因的基础上，研究了价格大战对电商企业的有利和不利影响，论述了价格大战对网络营销绩效发生影响的根源性原因，据此针对性地提出提高网络营销绩效的相应建议措施。%The frequent e-business price war has drawn extensive attention, which has great influence on the network marketing performance of relevant enterprises. Based on the analysis of the causes of electric business price war, this paper researches its favorable and unfavorable effects and the reasons for its influence on network marketing performance. On this basis, it puts forward some corresponding measures to improve network marketing performance.
Michael Alles; Srikant Datar
1998-01-01
Most research into cost systems has focused on their motivational implications. This paper takes a different approach, by developing a model where two oligopolistic firms strategically select their cost-based transfer prices. Duopoly models frequently assume that firms game on their choice of prices. Product prices, however, are ultimately based on the firms' transfer prices that communicate manufacturing costs to marketing departments. It is for this reason that transfer prices will have a s...
Krueger, Malte
2009-01-01
The pricing of payments has received increasing attention of regulators. In many cases, regulators are concerned that consumers do not face cost based prices. They argue that without cost based prices consumers will make inefficient choices. In this paper, it is argued that both, economics of scale and the particular laws governing pricing in two-sided markets provide a case against cost based pricing.
Marginal pricing of transmission services: An analysis of cost recovery
Perez-Arriaga, I.J.; Rubio, F.J. [Univ. Pontificia Comillas, Madrid (Spain); Puerta, J.F.; Arceluz, J.; Marin, J. [IBERDROLA, Bilbao (Spain). Unidad de Planificacion Estrategica
1995-02-01
This paper presents an in-depth analysis of network revenues computed with marginal pricing, and in particular it investigates the reasons why marginal prices fail to recover the total incurred network costs in actual power systems. The basic theoretical results are presented and the major causes of the mismatch between network costs and marginal revenues are identified and illustrated with numerical examples, some tutorial and others of realistic size. The regulatory implications of marginal network pricing in the context of competitive electricity markets are analyzed, and suggestions are provided for the meaningful allocation of the costs of the network among its users.
ACCOUNTING ASPECTS OF PRICING AND TRANSFER PRICING
TÜNDE VERES
2011-01-01
The pricing methods in practice need really complex view of the business situation and depend on the strategy and market position of a company. The structure of a price seems simple: cost plus margin. Both categories are special area in the management accounting. Information about the product costs, the allocation methodologies in cost accounting, the analyzing of revenue and different level of the margin needs information from accounting system. This paper analyzes the pricing methods from m...
Accounting Aspects of Pricing and Transfer Pricing
TÜNDE VERES
2011-01-01
The pricing methods in practice need really complex view of the business situation and depend on the strategy and market position of a company. The structure of a price seems simple: cost plus margin. Both categories are special area in the management accounting. Information about the product costs, the allocation methodologies in cost accounting, the analyzing of revenue and different level of the margin needs information from accounting system. This paper analyzes the pricing methods from m...
Research on Stock Price Reversal Points Prediction Based on BP Neural Network%基于BP神经网络的股票价格反转点预测
王建国
2015-01-01
The stock market has an important role in the whole financial market and the prediction of the stock price reversal point is one of the most abstractive and the most significant research topic. And the BP neural network which has been proved to be the ability of achieving any nonlinear mapping function whatever its complexity ,is very suitable for resolving the problem with a complex internal mechanism such as stock price prediction. Aims to achieve stock price reversal points prediction with BP model.%股票市场在整个金融市场中起着很重要的作用。而股票价格反转点的预测是最具有吸引力并且有意义的研究问题之一。 BP神经网络作为已被证明为具有实现任何复杂非线性映射的功能的多层预测模型特别适合于求解股票预测之类的内部机制复杂的问题。旨在利用BP神经网络模型的预测能力实现对股票价格的反转点预测。
Price strategy and pricing strategy: terms and content identification
Panasenko Tetyana
2015-01-01
The article is devoted to the terminology and content identification of seemingly identical concepts "price strategy" and "pricing strategy". The article contains evidence that the price strategy determines the direction, principles and procedure of implementing the company price policy and pricing strategy creates a set of rules and practical methods of price formation in accordance with the pricing strategy of the company.
Pricing products: juxtaposing affordability with quality appeal.
1984-01-01
Choosing appropriate product prices is 1 of the most crucial steps in creating an effective contraceptive social marketing (CSM) sales campaign. The Social Marketing Forum conducted an informal survey of social marketing project managers, international contractors, and marketing consultants to determine how CSM programs cope with pricing problems and ways to circumvent some obstacles. According to Diana Altman, a family planning consultant, low prices that make products available to needy individuals are more important than the program's self sufficiency, yet if prices are too low, consumers think the products were unusable in the US and thus were dumped on local markets. Other key factors include commercial competition, spiraling inflation rates, and problems with rising prices and retailer/distributor margins. A sampling of per capita gross national products indicates the poverty level of most CSM projects' target market. Consequently, CSM projects must set low pices, regardless of program operating costs. The goal often is to increase the demand and availability for contraceptives. The fact that social marketing products must pass through retail networks to reach consumers complicates the pricing equation. To deal with the problem, India's Nirodh program gives a 25% margin to distributors/wholesalers, compared to 6% offered on most other goods. Retailers also receive a 25% margin, more than double the commercial rate. Once prices are set, increases pose hazards. Local government approval often is a prerequisite and can require lengthy negotiations. Market studies remain a valuable approach to effective pricing, according to PNA's Mallamad and other research consultants. They cite such effective research strategies as test marketing products and asking consumers how prices affect buying habits. Further, CSM projects can jump over some pricing hurdles through creative marketing. An effective pricing strategy alone cannot produce a successful CSM program. Pricing
Research on Pricing Strategy of Online Group Buying in Two-sided Network%双边网络环境下的网络团购定价策略研究
唐方成; 池坤鹏
2013-01-01
Online group buying is a business model characterized with two-sided market.The challenging problems that group buying firms face are how to meet the needs of consumers and suppliers and how to develop the right bilateral price structure and pricing level.According to the nature of two-sided markets group purchase site,this paper constructs the pricing models by considering multi-homing of consumers and suppliers.Furthermore,the pricing models under the monopoly pattern and competition equilibrium are presented.This study investigates the effect of some key factors of platform fixed cost,search matching,degree of service differentiation and cross-group network effects change on pricing mechanism.Finally,a case study of Lashou is employed to test the proposed pricing mechanism and tactics.%网络团购是一种典型的具有双边市场特征的商业模式,如何满足消费者和商户的需求,合理制定双边价格结构和定价水平已成为团购网站运营企业面临的挑战性问题.本文应用双边市场理论,构建了网络团购双边客户多归属条件下的定价模型,分析了垄断模式和竞争均衡状态下的定价机制,并讨论了网站固定成本、搜索匹配度、服务差异化程度以及交叉网络效应等关键因素变化对网络团购平台企业定价策略的影响.最后,通过拉手网的案例分析佐证了文中提出的定价机制与策略.
Pricing strategies under heterogeneous service requirements
Mandjes, Michel
2003-01-01
This paper analyzes a communication network with heterogeneous customers. We investigate priority queueing as a way to differentiate between these users. Customers join the network as long as their utility (which is a function of the queueing delay) is larger than the price of the service. We focus
Juan David Velásquez Henao
2007-12-01
Full Text Available En este artículo, se modela el precio promedio mensual del café colombiano en la Bolsa de Nueva York, usando varios modelos alternativos. El modelo final seleccionado está compuesto por una componente lineal autorregresiva más una red neuronal artificial tipo perceptron multicapa con dos neuronas en la capa oculta, que permite representar la dinámica que sigue el valor esperado de la serie de precios; mientras que la dinámica de los residuales es especificada usando un proceso heterocedástico condicional autoregresivo de primer orden. Los residuales normalizados del modelo son incorrelacionados y homocedásticos, y siguen aproximadamente una distribución normal. Los resultados indican que el precio actual depende de los precios ocurridos en los últimos cuatro meses.In this paper, the monthly average price of the Colombian coffee in the New York Stock Exchange, is modelling by means of several alternative models. The preferred model is composed by a lineal autoregressive component plus a multilayer perceptron neural network with two neurons in the hidden layer, that allow us to representing the dynamic following by the expected value of the price time series; while, the dynamic of the residuals is specified by an autoregressive conditional heterocedastic model of first order. The normalized residuals of the preferred model are uncorrelated, homocedastic and are distributed following a normal distribution. The results indicate that the current price depend of the prices in the previous four months.
Outlier Edge Detection Using Random Graph Generation Models and Applications
Zhang, Honglei; Gabbouj, Moncef
2016-01-01
Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Prefe...
Pels, Eric; Verhoef, Erik T.
2003-01-01
Conventional economic wisdom suggests that congestion pricing would be an appropriate response to cope with the growing congestion levels currently experienced at many airports. Several characteristics of aviation markets, however, may make naive congestion prices equal to the value of marginal travel delays a non-optimal response. This paper has developed a model of airport pricing that captures a number of these features. The model in particular reflects that airlines typically have market power and are engaged in oligopolistic competition at different sub-markets; that part of external travel delays that aircraft impose are internal to an operator and hence should not be accounted for in congestion tolls. We presented an analytical treatment for a simple bi-nodal symmetric network, which through the use of 'hyper-networks' would be readily applicable to dynamic problems (in discrete time) such as peak - off-peak differences, and some numerical exercises for the same symmetric network, which was only designed to illustrate the possible comparative static impacts of tolling, in addition to marginal equilibrium conditions as could be derived for the general model specification. Some main conclusions are that second-best optimal tolls are typically lower than what would be suggested by congestion costs alone and may even be negative, and that the toll as derived by Brueckner (2002) may not lead to an increase in total welfare. While Brueckner (2002) has made clear that congestion tolls on airports may be smaller than expected when congestion costs among aircraft are internal for a firm, our analysis adds to this that a further downward adjustment may be in order due to market power. The presence of market power (which causes prices to exceed marginal costs) may cause the pure congestion toll to be suboptimal, because the resulting decrease in demand is too high (the pure congestion tall does not take into account the decrease in consumer surplus). The various
王建华; 李南; 罗建强; 郭慧
2011-01-01
In a price-sensitive supply chain, each business partner as independent profit unit defines the relationship between batch order and ordering price based on members' profit preferences and resource conditions. The ordering quality of products is strongly related to a member' s price decision-making processes for purchasing, supplying, production, logistics and selling activities. The operating cost and profit of a supply chain is different from that of total product quantity and distribution. Planning can reduce operating cost and improve profitability and market competitiveness for a price-sensitive supply chain. An effective planning can further lower resource consumption and make contributions to sustainable development of society and economy.This research studies a four-stage price-sensitive supply chain consisting of multiple suppliers, one manufacturer, multiple distribution centers and multiple retailers. A manufacturer needs to make decisions on supply chain network planning activities, such as supplier selection for parts and logistics support, sourcing from different suppliers, and distribution and selling of final products via different retailers. The network planning problem is complicated and requires supply chain managers apply a good decision-making algorithm to obtain a satisfactory solution on a timely basis.We first build an integer non-linear planning (INLP) model to represent network planning problems. We then use the heuristic repair method embedded with the hybrid genetic algorithm ( HCA ) to resolve the model. Finally, we use simulations to verify the model validity, as well as the stability and efficiency of the algorithm. It is essential to build a general structure model and mathematical model for optimizing supply chain planning due to the multi-forms of actual supply chains.In the first part, we describe the planning problem in detail, and design a general structure model for supply chains to represent the relationships among the members
Study of cascading failure-oriented attack on the edges of complex networks%面向相继故障的复杂网络上边袭击策略研究
王建伟; 荣莉莉
2011-01-01
In order to discuss cascading failures on complex networks subject to attacks, this paper adopts a cascading failure model presented in Physical Review E 77, 026101(2008), compares the universal cascading failure phenomena on BA scale-free and WS small-world networks subject to two different attacks on edges,and explores the effects of network structures on edge attack strategies. Both theoretical analysis and numerical simulations indicate that the attack on the edges with the lowest loads is more prone to trigger cascading failures than the attack on the ones with the highest loads in the certain range of the tunable parameter, and the difference network structures have much important effects on attack strategies.%针对复杂网络遭遇蓄意攻击引发的相继故障问题,采用Physical Review E77,026101(2008)所提出的相继故障模型,对比了BA无标度网络和WS小世界网络上遭遇两种边袭击策略导致的全局相继故障现象,并探讨了网络拓扑结构对边袭击策略的影响.理论解析和数值模拟均表明了在模型中可调参数的一定取值内,袭击网络中负荷最小的边比袭击网络中负荷最大的边更易于导致相继故障现象,而且,网络拓扑结构的不同对袭击策略也有着非常重要的影响.
曾鸣; 马少寅; 王蕾; 刘宏志; 薛松
2011-01-01
分布式电源接入系统会对配电网线损产生重要影响，随着分布式电源并网发电规模化发展，合理分摊配电网线损成为当前需要解决的重要问题之一。构建了一种基于节点因子定价的含分布式电源并网的配电网线损分摊模型，通过交易盈余来弥补线损成本，在电力用户间分摊剩余费用，从而降低边际损失，通过对某区域配电网的模拟仿真验证了本文所提出方法的合理性和可行性。%The integration of distributed generation into distribution network has great impact on the loss allocations of the network system. With the large-scale development of grid-connected distributed generation, the reasonable loss allocation has become an important problem to be addressed. In this paper, a loss allocation model in distribution network with distributed generation is established based on nodal price. The nodal price is to make up for loss cost by merchandise surplus, which allocates residual expenses so as to reduce the marginal loss. The simulation results of a regional distribution network show that the proposed method is reasonable and feasible.
Stacey, Brian
2015-01-01
Price discrimination enjoys a long history in the airline industry. Borenstein (1989) discusses price discrimination through frequent flyer programs from 1985 as related to the Piedmont-US Air merger, price discrimination strategies have grown in size and scope since then. From Saturday stay over requirements to varying costs based on time of purchase, the airline industry is uniquely situated to enjoy the fruits of price discrimination.
基于在线评分和网络效应的应用软件定价策略%Software Pricing Strategy under Online Rating and Network Effect
刘洋; 廖貅武
2013-01-01
Online rating offers users more product information , and the number of rating users influences the user utility .Based on the information goods pricing theory and game theory , and taking software on platforms such as APP Store and Android Market as the research sample , this paper develops a two-period economic model to explore the optimal pricing strategy of monopoly ap-plication software developers under online rating mechanisms and network effect of information goods .Results show that: when real software quality is lower than users′expectation, the rating truly signals software quality.Meanwhile, software developers′optimal choice is to price high in the first period and lower the price thereafter if the network effect is weak , while software devel-opers′optimal choice is to price low even free to attract more users in the first period and raise price for more profits in the second period if the network effect is strong .When real software quality is not lower than users′expectation , rating restricts the informa-tion signal of the software with high quality .Then users can only assume that the software quality equals to their expectation , so software developers′optimal quality choice is equal to users′expected quality .Finally, this paper discusses limitations as well as flaws of the ratings range .To maximize profit , software developers need some marketing strategies such as platform promotion to boost users′willingness to pay .%在线评分可以为用户提供更多的产品信息，同时评分人数的多少也会影响用户效用。以 APP Store、Android Market 等平台上的应用软件为研究对象，以信息产品定价理论和博弈论为理论基础，通过建立两阶段的经济学模型，研究在线评分机制和信息产品网络效应的共同作用下垄断应用软件开发者的最优产品定价策略。研究结果表明，当软件质量低于用户事前期望、评分传递的质量信号较真实时，若
Price control and macromarketing
Kancir Rade
2003-01-01
Full Text Available Price control at macro level is part of integral macro marketing strategic control system, or more precisely, part of social marketing mix control. Price impact is direct, if it is regarded in the context of needs satisfaction, and indirect, within the context of resource allocation. These two patterns of price impact define control mechanism structuring. Price control in sense of its direct impact at process of need satisfaction should comprise qualitative and quantitative level of needs satisfaction at a given price level and its structure, informational dimension of price and different disputable forms of corporate pricing policies. Control of price allocation function is based at objectives of macro marketing system management in the area of resource allocation and the role of price as allocator in contemporary market economies. Control process is founded, on one hand, at theoretical models of correlation between price and demand in different market structures, and on the other hand, at complex limits that price as allocator has, and which make whole control process even more complex because of reduction of the degree of determinism in functioning of contemporary economic systems. Control of price allocation function must be continuous and dynamic process if it is to provide for convergence with environmental changes and if it is to provide for placing control systems at micro marketing levels in the function of socially valid objectives.
Regulation of Pharmaceutical Prices
Kaiser, Ulrich; Mendez, Susan J.; Rønde, Thomas
the joint eects of this reform on prices and quantities. Prices decreased more than 26 percent due to the reform, which reduced patient and government expenditures by 3.0 percent and 5.6 percent, respectively, and producer revenues by 5.0 percent. The prices of expensive products decreased more than...
Valuation Struggles over Pricing
Pallesen, Trine
2016-01-01
public goods into play, all the while prompting a translation of these values into a single price. Following the struggles over the pricing of wind power in the early 2000s, the study illustrates that rather than a pollution of the market sphere by that of politics, a politics of pricing can be observed...
Dutch house price fundamentals
Haffner, M.E.A.; de Vries, P.
2009-01-01
This paper discusses house price developments in the Netherlands, specifically focussing on the question whether current house prices in the Dutch owner-occupied market are likely to decrease. We analyse three aspects of the question based on a literature review: (1) whether there is a house price b
Dutch house price fundamentals
Haffner, M.E.A.; de Vries, P.
2009-01-01
This paper discusses house price developments in the Netherlands, specifically focussing on the question whether current house prices in the Dutch owner-occupied market are likely to decrease. We analyse three aspects of the question based on a literature review: (1) whether there is a house price
无
2004-01-01
The price raise in natural resources is inevitable. At present, building ceramic industry is facing the pressure brought by price raise in raw material. Marketing directors still hesitate whether the price of ceramic tiles should be raised. The crisis brought by social environment made the employees care-laden.
Listed Company’s Social Network and Its Impact on IPO Pricing%上市公司社会网络及其对IPO定价效率的影响
史欣向; 肖旦; 王满四
2015-01-01
现有研究大多关注显性的、正式层面因素，而鲜有关注隐性的、非正式层面因素，如企业社会网络对IPO抑价的影响。文章以200家新上市公司公开披露的资料为基础，建立了一个200×200共计40000个单元的0-1矩阵，利用Ucinet社会网络分析软件量化分析了中国上市公司的社会网络特征——网络密度、小团体、中心性及中介性。然后，以此为基础利用随机边界模型检验了社会网络对IPO定价效率的作用。研究结果表明，在一级市场上，故意抑价是存在的。如果企业加入了某个“小团体”或者在网络中占据着“媒介”地位，则会更倾向于实施“故意抑价”。如果企业在网络中的地位较高，则会较少采取“故意抑价”。在二级市场上，尽管“价格虚高”是存在的，但是没有经验证据表明社会网络会对价格虚高产生显著影响。文章对企业社会网络的量化研究以及对IPO抑价形成原因的全新解释，均具有一定的创新性和启发性。%Most of the existing studies focus on explicit and formal factors,while there are few researches to consider about the effect of hidden and informal factors such as the impact of listed company’s social network on IPO underpricing. Based on publicly disclosed information of 200 new listed companies, this paper employs Ucinet social network analysis software to make a quantitative study on characteristics of Chinese listed company’s social network including network density,special groups,centrality and mediation by building a 0-1 matrix with 200 x 200 in total of 40000 units. Then,the paper,in accor⁃dance with the above work, applies stochastic frontier model to test the impact of social network on IPO pricing efficiency. The results show that there is“deliberate underpricing”in the stock-publishing market. And,if a company joins in a“spe⁃cial group”or occupies a“bridge”position in the
Netseva-Porcheva Tatyana
2010-01-01
Full Text Available The main aim of the paper is to present the value-based pricing. Therefore, the comparison between two approaches of pricing is made - cost-based pricing and value-based pricing. The 'Price sensitively meter' is presented. The other topic of the paper is the perceived value - meaning of the perceived value, the components of perceived value, the determination of perceived value and the increasing of perceived value. In addition, the best company strategies in matrix 'value-cost' are outlined. .
Dutch house price fundamentals
Haffner, M.E.A.; De Vries, P.
2009-01-01
This paper discusses house price developments in the Netherlands, specifically focussing on the question whether current house prices in the Dutch owner-occupied market are likely to decrease. We analyse three aspects of the question based on a literature review: (1) whether there is a house price bubble ready to burst; (2) whether house prices will decline in response to the credit crisis that started in 2007; and (3) whether it is likely that house prices will decrease as a result of reform...
郭强; 姚晓玲
2016-01-01
从消费者效用角度研究了一个网络音乐厂商与一个传统音乐厂商构成的双寡头垄断市场中的产品定价策略，构建Hotelling博弈模型，探讨了网络外部性对音乐厂商最优定价、利润变化趋势和市场盗版水平的影响。研究发现：有网络外部性时，不论网络音乐厂商还是传统音乐厂商，产品价格都上升；网络音乐厂商的利润必然上升，而传统音乐厂商的利润可能下降。网络外部性的存在增大了整个音乐市场的需求，盗版的需求也随之增大，但市场竞争加剧导致盗版市场份额可能下降。%From the perspective of consumer utility , this paper constructs a Hotelling model which is based on the network externality to discuss a product pricing strategy in a double oligopoly market consisting an online music producer and a tradi -tional music producer .Result finds that the price of these two producers will rise in the presence of network externality .The profit of the online music producer will increase , and the profit of the traditional music producer may decrease .In addition, the existence of network externality increases the demand of the whole music market and the demand of piracy .However , the market competition intensifies and the market share of piracy demands falls .
Dynamic Evolution of Financial Network and its Relation to Economic Crises
Gao, Ya-Chun; Wei, Zong-Wen; Wang, Bing-Hong
2013-02-01
The static topology properties of financial networks have been widely investigated since the work done by Mantegna, yet their dynamic evolution with time is little considered. In this paper, we comprehensively study the dynamic evolution of financial network by a sliding window technique. The vertices and edges of financial network are represented by the stocks from S&P500 components and correlations between pairs of daily returns of price fluctuation, respectively. Furthermore, the duration of stock price fluctuation, spanning from January 4, 1985 to September 14, 2009, makes us to carefully observe the relation between the dynamic topological properties and big financial crashes. The empirical results suggest that the financial network has the robust small-world property when the time evolves, and the topological structure drastically changes when the big financial crashes occur. This correspondence between the dynamic evolution of financial network and big financial crashes may provide a novel view to understand the origin of economic crisis.
安进; 季一木
2016-01-01
针对传统社交网络社区推荐算法精度不高且计算复杂度过高的问题，提出一种弱连接边缘独立判别社交网络社区快速生成树检测算法，在提高社区推荐精度的同时，降低算法计算复杂度。首先，结合社交网络社区推荐特点，设计基于边缘重量分配节点相似性的最大生成树算法，实现对社交网络社区的有效检测；其次，针对所提算法，存在弱连接边缘重复添加、删除，浪费计算资源的问题，提出弱连接边缘独立判别的快速生成树检测算法，进一步提高算法的计算效率；最后，通过在标准测试数据库中的实验对比，验证了所提算法的有效性。%According to the problem of low accuracy and high computational complexity in traditional social network communi-ty recommendation algorithm,this paper proposed the weakly connected edge independent discriminant based rapid spanning tree algorithm for social network community detection,which could improve the community recommendation accuracy,and also reduced the computational complexity of the algorithm.Firstly,combined with the social network community characteristics,it designed the edge weight distribution node similar based maximum spanning tree algorithm,which realized the effective detec-tion of the social network community.Secondly,in order to solve the problem of proposed algorithm in the existence of weak connection that adding and deleting the weak edge could waste a lot of computing resources,it proposed the rapid spanning tree algorithm with weakly connected edge independent discrimination detection,which could further improve the efficiency of algorithm.Finally,through experiments in the standard test database,it verified the effectiveness of the proposed algorithm.
Calculating proper transfer prices
Dorkey, F.C. (Meliora Research Associates, Rochester, NY (United States)); Jarrell, G.A. (Univ. of Rochester, NY (United States))
1991-01-01
This article deals with developing a proper transfer pricing method. Decentralization is as American as baseball. While managers laud the widespread benefits of both decentralization and baseball, they often greet the term transfer price policy with a yawn. Since transfer prices are as critical to the success of decentralized firms as good pitchers are to baseball teams, this is quite a mistake on the part of our managers. A transfer price is the price charged to one division for a product or service that another division produced or provided. In many, perhaps most, decentralized organizations, the transfer pricing policies actually used are grossly inefficient and sacrifice the potential advantages of decentralization. Experience shows that far too many companies have transfer pricing policies that cost them significantly in foregone growth and profits.
Price learning during grocery shopping
Jensen, Birger Boutrup
of what consumers learn about prices during grocery shopping. Three measures of price knowledge corresponding to different levels of price information processing were applied. Results indicate that price learning does take place and that episodic price knowledge after store exit is far more widespread...... than expected. Consequently, a new view of how consumer price knowledge evolves during grocery shopping is presented....
方国敏; 徐玖平
2015-01-01
针对大型垄断厂商在商品生产、运输、定价决策中独立考虑生产定价和运输两个环节的弊端，提出一种将产量决策、运输决策和定价决策3个环节作为一个系统进行考虑的综合决策模型.借助利润网络图，构建同时考虑生产及运输成本以及市场需求的商品生产、运输和定价综合决策模型，并探讨模型的解法及其理论基础.通过给出的应用案例表明，相比传统决策模型，利用综合决策模型可以提高15.50%的利润.%For the drawbacks that research on production, transportation and pricing decision problems has typically focused on considering individual production/pricing problems, or on considering individual transportation problems, the integrated decision-making model is proposed. The production decisions, transportation decisions and pricing decision are considered as a system, and an integrated decision-making model considering simultaneously production cost, transportation cost and the market demand is proposed by using the profit network graph. The solution and its theoretical basis are discussed. An application example is given to illustrate that, by using the mode, the increase in total operating profit from tradition model is up to 15.50%.
The structure and resilience of financial market networks.
Peron, Thomas Kaue Dal'Maso; Costa, Luciano da Fontoura; Rodrigues, Francisco A
2012-03-01
Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.
Scale-Free Behavior in Weighted Stock Network
WAN Yang-song; CHEN Zhong; CHEN Xiao-rong
2007-01-01
A weighted stock network model of stock market is presented based on the complex network theory. The model is a weighted random network, in which each vertex denotes a stock, and the weight assigned to each edge is the cross-correlation coefficient of returns. Analysis of A shares listed at Shanghai Stock Exchange finds that the influence-strength (IS) follows a power-law distribution with the exponent of 2.58. The empirical analysis results show that there are a few stocks whose price fluctuations can powerfully influence the price dynamics of other stocks in the same market. Further econometric analysis reveals that there are significant differences between the positive IS and the negative IS.
Price strategy and pricing strategy: terms and content identification
Panasenko Tetyana
2015-11-01
Full Text Available The article is devoted to the terminology and content identification of seemingly identical concepts "price strategy" and "pricing strategy". The article contains evidence that the price strategy determines the direction, principles and procedure of implementing the company price policy and pricing strategy creates a set of rules and practical methods of price formation in accordance with the pricing strategy of the company.
Transfer pricing and the Czech tax policy
Veronika Solilová
2010-01-01
Full Text Available The Czech Republic as a small open economy with an extensive network of the international tax treaties for the avoidance of the double taxation prevents from shifting the tax base of the associated enterprises to countries with preferential tax regime through transfer pricing rules. Transfer pricing as one of the important areas of international taxes determines how the profits of the multinational enterprises are split between the jurisdictions in which they operate and which countries get to tax those profits. This situation may affect the global budget of the multinational enterprises and the tax revenues of the jurisdictions. This paper is focused on the transfer pricing rules used in the Czech Republic and makes recommendations for the Czech tax policy in this area based on the analysis of the transfer pricing rules in the EU Member States.
Alexander G. Kerl
2011-04-01
Full Text Available This study analyzes the accuracy of forecasted target prices within analysts’ reports. We compute a measure for target price forecast accuracy that evaluates the ability of analysts to exactly forecast the ex-ante (unknown 12-month stock price. Furthermore, we determine factors that explain this accuracy. Target price accuracy is negatively related to analyst-specific optimism and stock-specific risk (measured by volatility and price-to-book ratio. However, target price accuracy is positively related to the level of detail of each report, company size and the reputation of the investment bank. The potential conflicts of interests between an analyst and a covered company do not bias forecast accuracy.
Rolf Turner
2014-07-01
Full Text Available We describe an R package for determining the optimal price of an asset which is perishable in a certain sense, given the intensity of customer arrivals and a time-varying price sensitivity function which speci?es the probability that a customer will purchase an asset o?ered at a given price at a given time. The package deals with the case of customers arriving in groups, with a probability distribution for the group size being speci?ed. The methodology and software allow for both discrete and continuous pricing. The class of possible models for price sensitivity functions is very wide, and includes piecewise linear models. A mechanism for constructing piecewise linear price sensitivity functions is provided.
Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C., E-mail: jaime.esquivel@fi.uaemex.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2011-11-15
The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)
Zhang, Xiuyun; Xin, John; Ding, Feng
2013-04-01
The edge of two dimensional (2D) graphene, as the surface of a three dimensional (3D) crystal, plays a crucial role in the determination of its physical, electronic and chemical properties and thus has been extensively studied recently. In this review, we summarize the recent advances in the study of graphene edges, including edge formation energy, edge reconstruction, method of graphene edge synthesis and the recent progress on metal-passivated graphene edges and the role of edges in graphene CVD growth. We expect this review to provide a guideline for readers to gain a clear picture of graphene edges from several aspects, especially the catalyst-passivated graphene edges and their role in graphene CVD growth.
Customizing Prices in Online Markets
Reinartz, Werner
2002-01-01
Dynamic pricing is the dynamic adjustment of prices to consumers depending on the value these customers attribute to a good. Underlying the concept of dynamic pricing is what marketers call price customization. Price customization is the charging of different prices to end consumers based on a discriminatory variable. Internet technology will serve as a great enabling tool for making dynamic pricing accessible to many industries.
李留闯; 田高良; 马勇; 李彬
2012-01-01
在中国上市公司中普遍存在连锁董事的背景下,从公司透明度和趋同性两方面分析连锁董事对公司股价与市场波动之间的关系,采用实证方法进行检验,并进一步分析连锁董事对股价同步性波动的作用机制.以2003年至2010年中国上市公司为样本构建纵列截面数据,借鉴网络分析方法,采用居中中心度、中介中心度和向量中心度度量公司的连锁董事.实证结果表明,拥有连锁董事公司的股价同步性波动更高；在网络中镶嵌越紧密的公司,其股价波动和市场波动更一致.进一步研究还发现,在大公司和国有控制公司中,连锁董事通过降低公司透明度增加股价同步性波动；在小公司和非国有控制公司中,连锁董事通过增加公司间的趋同性增加股价同步性波动.研究结论对提高资本市场的效率有重要的政策意义.%Interlocking directorates is a very frequently observed characteristic among Chinese public enterprises. This study analyzes the relation between the interlocking directorate, stock price and market volatility from enterprise transparency and convergence and examines the impact of the interlocking directorate on stock price synchronicity. Based on panel data of Chinese public enterprises from 2003 to 2010 and social network analysis, this study uses degree centrality, betweenness centrality and eigenvector centrality to measure the interlocking directorate of enterprises. Our results showed that the stock price synchronicity of enterprises with interlocking directorates was higher than that without interlocking directorates. The market and stock price volatility of enterprises with high embeddness in the networks were more consistent. We also found that interlocking directorate improved stock price synchronicity by lowering transparency for state-owned and large enterprises and increasing convergence for non-state-owned and small enterprises. This paper contribute to
Relating price strategies and price-setting practices
Ingenbleek, P.T.M.; Lans, van der I.A.
2013-01-01
Purpose - This article addresses the relationship between price strategies and price-setting practices. The first derive from a normative tradition in the pricing literature and the latter from a descriptive tradition. Price strategies are visible in the market, whereas price-setting practices are h
Point of Connection Transmission Pricing in India
Soonee, S. K.; Barpanda, S. S.; Joshi, Mohit; Mishra, Nripen; Bhardwaj, Vaishally
2013-05-01
The National Electricity Policy (NEP) [1], issued by the Government of India, mandates transmission prices to be distance and direction sensitive and capture utilization of the network by each network user. In line with the mandate, the Central Electricity Regulatory Commission (CERC) [2] has issued Sharing of Interstate Transmission Charges and Losses Regulations, 2010 [3], to introduce point of connection (PoC)-based transmission pricing methodology in India. The methodology under the above regulations introduces one of the major reforms of its kind in the Indian power sector and seeks to share the total transmission charges in proportion to respective utilization of the transmission system by different entities. In this paper, the authors have enumerated their experience gained from the implementation of PoC-based transmission pricing regime in India. Authors have also discussed various issues encountered in the process of implementation and the methodology adopted.
Rose M. Baker
2016-05-01
Full Text Available Reviewed in this article is the potential for Massive Open Online Courses (MOOCs to transform higher education delivery, accessibility, and costs. Next, five major value propositions for MOOCs are considered (headhunting, certification, face-to-face learning, personalized learning, integration with services external to the MOOC, marketing. Then, four pricing strategies for MOOCs are examined (cross-subsidy, third-party, “freemium”, nonmonetary. Although the MOOC movement has experienced growing pains similar to most innovations, we assert that the unyielding pace of improvements in network technologies combined with the need to tame the costs of higher education will create continuing demand for MOOC offerings.
Community Detection Using Multilayer Edge Mixture Model
Zhang, Han; Lai, Jian-Huang; Yu, Philip S
2016-01-01
A wide range of complex systems can be modeled as networks with corresponding constraints on the edges and nodes, which have been extensively studied in recent years. Nowadays, with the progress of information technology, systems that contain the information collected from multiple perspectives have been generated. The conventional models designed for single perspective networks fail to depict the diverse topological properties of such systems, so multilayer network models aiming at describing the structure of these networks emerge. As a major concern in network science, decomposing the networks into communities, which usually refers to closely interconnected node groups, extracts valuable information about the structure and interactions of the network. Unlike the contention of dozens of models and methods in conventional single-layer networks, methods aiming at discovering the communities in the multilayer networks are still limited. In order to help explore the community structure in multilayer networks, we...
Modeling UK Natural Gas Prices when Gas Prices Periodically Decouple from the Oil Price
2015-01-01
When natural gas prices are subject to periodic decoupling from oil prices, for instance due to peak-load pricing, conventional linear models of price dynamics such as the Vector Error Correction Model (VECM) can lead to erroneous inferences about cointegration relationships, price adjustments and relative values. We propose the use of regime-switching models to address these issues. Our regime switching model uses price data to infer whether pricing is oil-driven (integrated) or gas-specific...
Price learning during grocery shopping
Jensen, Birger Boutrup
Many attempts have been made to measure consumers' price knowledge for groceries. However, the results have varied considerably and conflict with results of reference price research. This is the first study to examine price knowledge before, during, and after store visit, thus enabling a study...... of what consumers learn about prices during grocery shopping. Three measures of price knowledge corresponding to different levels of price information processing were applied. Results indicate that price learning does take place and that episodic price knowledge after store exit is far more widespread...... than expected. Consequently, a new view of how consumer price knowledge evolves during grocery shopping is presented....
Price Discrimination in Academic Journals.
Joyce, Patrick; Merz, Thomas E.
1985-01-01
Analysis of price discrimination (charging different prices to different customers for same product) for 89 academic journals in 6 disciplines reveals: incidence of price discrimination rose between 1974 and 1984, increase in mean institutional (library) subscription price exceeded increase in mean individual subscription price. Journal list…
Stability of edge states and edge magnetism in graphene nanoribbons
Kunstmann, Jens; Özdoğan, Cem; Quandt, Alexander; Fehske, Holger
2010-01-01
We critically discuss the stability of edge states and edge magnetism in zigzag edge graphene nanoribbons (ZGNRs). We point out that magnetic edge states might not exist in real systems, and show that there are at least three very natural mechanisms - edge reconstruction, edge passivation, and edge closure - which dramatically reduce the effect of edge states in ZGNRs or even totally eliminate them. Even if systems with magnetic edge states could be made, the intrinsic magnetism would not be ...
Oil prices and the stock prices of alternative energy companies
Henriques, Irene; Sadorsky, Perry [Schulich School of Business, 4700 Keele Street, Toronto, Ontario (Canada)
2008-05-15
Energy security issues coupled with increased concern over the natural environment are driving factors behind oil price movements. While it is widely accepted that rising oil prices are good for the financial performance of alternative energy companies, there has been relatively little statistical work done to measure just how sensitive the financial performance of alternative energy companies are to changes in oil prices. In this paper, a four variable vector autoregression model is developed and estimated in order to investigate the empirical relationship between alternative energy stock prices, technology stock prices, oil prices, and interest rates. Our results show technology stock prices and oil prices each individually Granger cause the stock prices of alternative energy companies. Simulation results show that a shock to technology stock prices has a larger impact on alternative energy stock prices than does a shock to oil prices. These results should be of use to investors, managers and policy makers. (author)
Gjedsted Nielsen, Mads
This paper is the first to consider a large scale natural experiment to estimate the effect of taxes on house prices. We find that a 1 percentage-point increase in income tax rates lead to a drop in house prices of at most 2.2%. This corresponds to a tax capitalization for the average household o...
Manufacturer's Suggested Retail Prices
Rosenkranz, S.
2003-01-01
Based on arguments of the `reference- dependent' theory of consumer choice we assume that a retailer's discount of a manufacturer's suggested retail price changes consumers' demand. We can show that the producer benefits from suggesting a retail price. If consumers are additionally sufficiently `los
Poverty and price transmission
Elleby, Christian
A key parameter determining the welfare impact from a world market shock is the transmission elasticity which measures the average domestic response to an international price change. Many studies have estimated price transmission elasticities for a large number of countries but the variation in t...
无
2007-01-01
@@ As was projected in the third-quarter monetary policy implementation report published by the People's Bank of China on November 15th, 2006, the residents' consumption price index in China would reach 1.5% in 2006. Prices of consumer commodities such as water, power and natural gas would rise and the pressure of inflation would persist in the future.
2010-01-01
@@ Cotton prices have received a lot of attention recently.Cotton Incorporated especically designed this Special Edition of Supply Chain Insights to frame the discussion concerning prices throughout the cotton supply chain in terms of the cyclical events that contributed to recent volatility and how a return to long-term averages over time can be expected.
Nazliben, Kamil
2015-01-01
The dissertation consists of three chapters that represent separate papers in the area of asset pricing. The ﬁrst chapter studies investors optimal asset allocation problem in which mean reversion in stock prices is captured by explicitly modeling transitory and permanent shocks. The second chapter
FEWS NET Price Volatility Data 2002-2012
US Agency for International Development — This dataset from the Famine Early Warning System Network (FEWS NET) documents ten years, from 2002 to 2012, of cereal price fluctuations across twenty-five African...
Tolerance of edge cascades with coupled map lattices methods
Cui Di; Gao Zi-You; Zheng Jian-Feng
2009-01-01
This paper studies the cascading failure on random networks and scale-free networks by introducing the tolerance parameter of edge based on the coupled map lattices methods. The whole work focuses on investigating some indices including the number of failed edges, dynamic edge tolerance capacity and the perturbation of edge. In general, it assumes that the perturbation is attributed to the normal distribution in adopted simulations. By investigating the effectiveness of edge tolerance in scale-free and random networks, it finds that the larger tolerance parameter 位 can more efficiently delay the cascading failure process for scale-free networks than random networks. These results indicate that the cascading failure process can be effectively controlled by increasing the tolerance parameter A. Moreover, the simulations also show that, larger variance of perturbation can easily trigger the cascading failures than the smaller one. This study may be useful for evaluating efficiency of whole traffic systems, and for alleviating cascading failure in such systems.
Price Formation by Bargaining and Posted Prices
Kultti, K.K.
1997-01-01
We study markets with two types of agents. Sellers have an indivisible good for sale, and their reservation value is zero. Buyers are randomly matched with sellers, and they value the good at unity. Sellers may be matched with any positive number of buyers, and they may choose to determine the price
曹桓
2014-01-01
LTE higher bandwidth and network capacity requirements will continue to drive technology innovation, average revenue per user will develop the great reversal, the price rate pack of communication services evolution and change will undoubtedly become the focus of attention. The cost of the business occupancy and network construction, remove redundant, focus on the core needs of two new perspectives of tariff packages evolutionary roadmap, combined with foreign cases and put forward implementation of the countermeasures.%LTE更高的带宽以及网络容量需求将不断地驱动技术变革，用户平均收入构成将发生巨大的逆转，资费套餐的演进和变化无疑将成为关注的焦点。文章从业务占用与网络建设成本，剔除冗余、关注核心需求两个新视角探讨了资费套餐的演进路线图，并结合国外案例提出了近期的对策与实施建议。
ALTERNATE PRICING STRATEGIES IN CONSTRUCTION
Krishna Mochtar
2000-01-01
Full Text Available Recent research findings on pricing strategies both in general and in construction are reviewed and explored. First%2C pricing strategy in general%2C mostly in the manufacturing industry%2C is reviewed. It includes the concepts of pricing strategy%2C predatory pricing%2C price wars%2C and price policy development. Second%2C pricing strategy in construction is explored. It includes various pricing models for bid price determination%2C such as the Friedman-Gates models%2C expected utility models%2C risk-pricing model%2C and the crew-day%2C multiple regression%2C and fuzzy-set pricing models. In conclusion%2C pricing strategies in construction are still predominantly based on a cost-based approach. More recent models try to close the gap between the models and the real life conditions of a bidder%5C%27s decision-making process. It appears that there are more problems in cost-based pricing as opposed to market-based pricing. Consequently%2C it is highly recommended that%2C alternative pricing approach such as that are closer to the proposed market-based pricing model need to be explored and developed for use in the construction industry. Abstract in Bahasa Indonesia : Pricing+strategy%2C+cost-based+pricing%2C+market-based+pricing.
7 CFR 1030.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1030.50 Section 1030.50 Agriculture Regulations of the Department of Agriculture (Continued... prices, and advanced pricing factors. See § 1000.50....
Influence of the time scale on the construction of financial networks.
Frank Emmert-Streib
Full Text Available BACKGROUND: In this paper we investigate the definition and formation of financial networks. Specifically, we study the influence of the time scale on their construction. METHODOLOGY/PRINCIPAL FINDINGS: For our analysis we use correlation-based networks obtained from the daily closing prices of stock market data. More precisely, we use the stocks that currently comprise the Dow Jones Industrial Average (DJIA and estimate financial networks where nodes correspond to stocks and edges correspond to none vanishing correlation coefficients. That means only if a correlation coefficient is statistically significant different from zero, we include an edge in the network. This construction procedure results in unweighted, undirected networks. By separating the time series of stock prices in non-overlapping intervals, we obtain one network per interval. The length of these intervals corresponds to the time scale of the data, whose influence on the construction of the networks will be studied in this paper. CONCLUSIONS/SIGNIFICANCE: Numerical analysis of four different measures in dependence on the time scale for the construction of networks allows us to gain insights about the intrinsic time scale of the stock market with respect to a meaningful graph-theoretical analysis.
Influence of the time scale on the construction of financial networks.
Emmert-Streib, Frank; Dehmer, Matthias
2010-09-30
In this paper we investigate the definition and formation of financial networks. Specifically, we study the influence of the time scale on their construction. For our analysis we use correlation-based networks obtained from the daily closing prices of stock market data. More precisely, we use the stocks that currently comprise the Dow Jones Industrial Average (DJIA) and estimate financial networks where nodes correspond to stocks and edges correspond to none vanishing correlation coefficients. That means only if a correlation coefficient is statistically significant different from zero, we include an edge in the network. This construction procedure results in unweighted, undirected networks. By separating the time series of stock prices in non-overlapping intervals, we obtain one network per interval. The length of these intervals corresponds to the time scale of the data, whose influence on the construction of the networks will be studied in this paper. Numerical analysis of four different measures in dependence on the time scale for the construction of networks allows us to gain insights about the intrinsic time scale of the stock market with respect to a meaningful graph-theoretical analysis.
A Framework for Price Statistics
Kimberly D. Zieschang
2000-01-01
This paper describes the primary framework associating the four principal price indices in the system of economic statistics—the Producer Price Index (PPI), the Consumer Price Index (CPI), and the Export and Import Price Indices (XPI and MPI)—with the macroeconomic value aggregates they decompose into price and volume components. The paper begins by defining the basic algebra of price indices. It then discusses the definition of the value aggregates comprising the goods and services component...
Asset Pricing - A Brief Review
Li, Minqiang
2010-01-01
I first introduce the early-stage and modern classical asset pricing and portfolio theories. These include: the capital asset pricing model (CAPM), the arbitrage pricing theory (APT), the consumption capital asset pricing model (CCAPM), the intertemporal capital asset pricing model (ICAPM), and some other important modern concepts and techniques. Finally, I discuss the most recent development during the last decade and the outlook in the field of asset pricing.
Edge-Disjoint Fibonacci Trees in Hypercube
Indhumathi Raman
2014-01-01
Full Text Available The Fibonacci tree is a rooted binary tree whose number of vertices admit a recursive definition similar to the Fibonacci numbers. In this paper, we prove that a hypercube of dimension h admits two edge-disjoint Fibonacci trees of height h, two edge-disjoint Fibonacci trees of height h-2, two edge-disjoint Fibonacci trees of height h-4 and so on, as subgraphs. The result shows that an algorithm with Fibonacci trees as underlying data structure can be implemented concurrently on a hypercube network with no communication latency.
王晓明; 李仕明; 倪得兵
2013-01-01
针对已有文献较孤立的关注网络外部性、多方参与以及服务质量对电信业务定价决策的影响这一不足,从用户的效用出发,推导出了网络外部性条件下的市场需求曲线,进而建立了网络外部性、企业相对市场关系、服务质量与电信业务价格之间的统一分析框架,考察了模型的均衡及其性质.结果表明:网络外部性和服务质量可以提高用户业务的支付费用并增加运营系统的利润.当网络外部性较弱时,参与企业双方同时决策意味着更优质的服务,更低的业务支付,更高的系统利润,而序贯决策则意味着决策先行者拥有先动者优势.当网络外部性较强时,服务提供商先行决策可以带来更优质的服务,更高的业务支付和系统利润,但作为决策追随者的运营商可以利用优质服务改善价值获取,获得后动者优势.%Focusing on the ignorance of co-impacts of network externality, other participants and service quality on telecom business price equilibrium, this paper derives the demand curve from consumers' utilities in the market with network externality. Then, establishes a unified analytical framework of telecom network externality, relative market relation, service quality and price, and makes further analysis about model equilibriums. The results show that both network externality and service quality increase the consumers pay and the profits of the operating system. When network externality is weaker, the decision-making simultaneously between service provider and telecom operator means even better services, less expenditures, and higher system profits, while the sequential decision-making means the first-mover advantage for the first decider. When network externality is stronger, service provider makes decision firstly can bring even better services, more expenditures and higher system profits. As a follower, operator can improve its value acquisition of the business, obtain after
Food Price Volatility and Decadal Climate Variability
Brown, M. E.
2013-12-01
The agriculture system is under pressure to increase production every year as global population expands and more people move from a diet mostly made up of grains, to one with more meat, dairy and processed foods. Weather shocks and large changes in international commodity prices in the last decade have increased pressure on local food prices. This paper will review several studies that link climate variability as measured with satellite remote sensing to food price dynamics in 36 developing countries where local monthly food price data is available. The focus of the research is to understand how weather and climate, as measured by variations in the growing season using satellite remote sensing, has affected agricultural production, food prices and access to food in agricultural societies. Economies are vulnerable to extreme weather at multiple levels. Subsistence small holders who hold livestock and consume much of the food they produce are vulnerable to food production variability. The broader society, however, is also vulnerable to extreme weather because of the secondary effects on market functioning, resource availability, and large-scale impacts on employment in trading, trucking and wage labor that are caused by weather-related shocks. Food price variability captures many of these broad impacts and can be used to diagnose weather-related vulnerability across multiple sectors. The paper will trace these connections using market-level data and analysis. The context of the analysis is the humanitarian aid community, using the guidance of the USAID Famine Early Warning Systems Network and the United Nation's World Food Program in their response to food security crises. These organizations have worked over the past three decades to provide baseline information on food production through satellite remote sensing data and agricultural yield models, as well as assessments of food access through a food price database. Econometric models and spatial analysis are used
Du, Pufeng; Wang, Lusheng
2014-01-01
One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278
Liu Lingli; Lü Jiahuan
2006-01-01
This article has suggested that high oil price could loom many years in the future and has analyzed the impact of this trend on the oil product mix and petroleum refining industry in China. This article has also put forward measures for sharpening the international competitive edge of China's petroleum refining industry to cope with the challenges of high oil price.
Tourism Equilibrium Price Trends
Mohammad Mohebi
2012-01-01
Full Text Available Problem statement: A review of the tourism history shows that tourism as an industry was virtually unknown in Malaysia until the late 1960s. Since then, it has developed and grown into a major industry, making an important contribution to the country's economy. By allocating substantial funds to the promotion of tourism and the provision of the necessary infrastructure, the government has played an important role in the impressive progress of the Malaysian tourism industry. One of the important factors which can attract tourists to Malaysia is the tourism price. Has the price of tourism decreased? To answer this question, it is necessary to obtain the equilibrium prices as well as the yearly trend for Malaysia during the sample period as it will be useful for analysis of the infrastructure situation of the tourism industry in this country. The purpose of the study is to identify equilibrium tourism price trends in Malaysian tourism market. Approach: We use hotel room as representative of tourism market. Quarterly data from 1995-2009 are used and a dynamic model of simultaneous equation is employed. Results: Based on the result during the period of 1995 until 2000, the growth rate of the equilibrium price was greater than consumer price index and producer price index. Conclusion: In the Malaysian tourism market, new infrastructure during this period had not been developed to keep pace with tourist arrivals.
Lee, Bruce Y; McGlone, Sarah M
2010-08-01
New vaccine pricing is a complicated process that could have substantial long-standing scientific, medical, and public health ramifications. Pricing can have a considerable impact on new vaccine adoption and, thereby, either culminate or thwart years of research and development and public health efforts. Typically, pricing strategy consists of the following ten components: 1. Conduct a target population analysis; 2. Map potential competitors and alternatives; 3. Construct a vaccine target product profile (TPP) and compare it to projected or actual TPPs of competing vaccines; 4. Quantify the incremental value of the new vaccine's characteristics; 5. Determine vaccine positioning in the marketplace; 6. Estimate the vaccine price-demand curve; 7. Calculate vaccine costs (including those of manufacturing, distribution, and research and development); 8. Account for various legal, regulatory, third party payer, and competitor factors; 9. Consider the overall product portfolio; 10. Set pricing objectives; 11. Select pricing and pricing structure. While the biomedical literature contains some studies that have addressed these components, there is still considerable room for more extensive evaluation of this important area.
Chalasani, P.; Saias, I. [Los Alamos National Lab., NM (United States); Jha, S. [Carnegie Mellon Univ., Pittsburgh, PA (United States)
1996-04-08
As increasingly large volumes of sophisticated options (called derivative securities) are traded in world financial markets, determining a fair price for these options has become an important and difficult computational problem. Many valuation codes use the binomial pricing model, in which the stock price is driven by a random walk. In this model, the value of an n-period option on a stock is the expected time-discounted value of the future cash flow on an n-period stock price path. Path-dependent options are particularly difficult to value since the future cash flow depends on the entire stock price path rather than on just the final stock price. Currently such options are approximately priced by Monte carlo methods with error bounds that hold only with high probability and which are reduced by increasing the number of simulation runs. In this paper the authors show that pricing an arbitrary path-dependent option is {number_sign}-P hard. They show that certain types f path-dependent options can be valued exactly in polynomial time. Asian options are path-dependent options that are particularly hard to price, and for these they design deterministic polynomial-time approximate algorithms. They show that the value of a perpetual American put option (which can be computed in constant time) is in many cases a good approximation to the value of an otherwise identical n-period American put option. In contrast to Monte Carlo methods, the algorithms have guaranteed error bounds that are polynormally small (and in some cases exponentially small) in the maturity n. For the error analysis they derive large-deviation results for random walks that may be of independent interest.
Sodhi, ManMohan S; Sodhi, Navdeep S
2005-05-01
Many companies are now good at managing costs and wringing out manufacturing efficiencies. The TQM movement and the disciplines of Six Sigma have seen to that. But the discipline so often brought to the cost side of the business equation is found far less commonly on the revenue side. The authors describe how a global manufacturer of industrial equipment, which they call Acme Incorporated, recently applied Six Sigma to one major revenue related activity--the price-setting process. It seemed to Acme's executives that pricing closely resembled many manufacturing processes. So, with the help of a Six Sigma black belt from manufacturing, a manager from Acme's pricing division recruited a team to carry out the five Six Sigma steps: Define what constitutes a defect. At Acme, a defect was an item sold at an unauthorized price. Gather data and prepare it for analysis. That involved mapping out the existing pricing-agreement process. Analyze the data. The team identified the ways in which people failed to carry out or assert effective control at each stage. Recommend modifications to the existing process. The team sought to decrease the number of unapproved prices without creating an onerous approval apparatus. Create controls. This step enabled Acme to sustain and extend the improvements in its pricing procedures. As a result of the changes, Acme earned dollar 6 million in additional revenue on one product line alone in the six months following implementation--money that went straight to the bottom line. At the same time, the company removed much of the organizational friction that had long bedeviled its pricing process. Other companies can benefit from Acme's experience as they look for ways to exercise price control without alienating customers.
Rowley, Jennifer; Butcher, David
1994-01-01
Considers comparative prices for bibliographic data on CD-ROM and in print. Topics addressed include differences in the nature of bibliographic data in the two media, the relative complexities of pricing structure, varying policies on network pricing, and standardization of the licensing arrangement. (KRN)
Rowley, Jennifer; Butcher, David
1994-01-01
Considers comparative prices for bibliographic data on CD-ROM and in print. Topics addressed include differences in the nature of bibliographic data in the two media, the relative complexities of pricing structure, varying policies on network pricing, and standardization of the licensing arrangement. (KRN)
Poverty and price transmission
Elleby, Christian
A key parameter determining the welfare impact from a world market shock is the transmission elasticity which measures the average domestic response to an international price change. Many studies have estimated price transmission elasticities for a large number of countries but the variation in t...... growth but the relationship is less significant. The finding that food prices in middle-income countries increased the most during the food crises is a cause for concern in light of the fact that the majority of the world's poor today live in middle-income countries....
Pasaribu, Rowland Bismark Fernando
2010-01-01
The Capital Asset Pricing Model (CAPM) has dominated finance theory for over thirty years; it suggests that the market beta alone is sufficient to explain stock returns. However evidence shows that the cross-section of stock returns cannot be described solely by the one-factor CAPM. Therefore, the idea is to add other factors in order to complete the beta in explaining the price movements in the stock exchange. The Arbitrage Pricing Theory (APT) has been proposed as the first multifactor succ...
Edgeworth Price Cycles, Cost-based Pricing and Sticky Pricing in Retail Gasoline Markets
Noel, Michael
2004-01-01
This paper examines dynamic pricing behavior in retail gasoline markets for 19 Canadian cities over 574 weeks. I find three distinct retail pricing patterns: 1. cost-based pricing, 2. sticky pricing, and 3. steep, asymmetric retail price cycles that, while seldom documented empirically, resemble those of Maskin & Tirole[1988]. Using a Markov switching regression, I estimate the prevalence of patterns and the structural characteristics of the cycles. Retail price cycles prevail in over 40% of ...
Dynamic Hybrid Model for Short-Term Electricity Price Forecasting
Marin Cerjan
2014-05-01
Full Text Available Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP neural network for forecasting electricity price and price spike detection. Based on statistical analysis, days are arranged into several categories. Similar days are examined by correlation significance of the historical data. Factors impacting the electricity price forecasting, including historical price factors, load factors and wind production factors are discussed. A price spike index (CWI is defined for spike detection and forecasting. Using proposed approach we created several forecasting models of diverse model complexity. The method is validated using the European Energy Exchange (EEX electricity price data records. Finally, results are discussed with respect to price volatility, with emphasis on the price forecasting accuracy.
白莹; 李明杰; 袁冲; 邓舒; 胡春
2012-01-01
双边市场理论是近年来产业组织研究的热点问题,结合网络团购平台特点,可以推导出适合网络团购平台的定价模型,讨论交叉网络外部性、差异化程度、卖方信誉及平台搜索匹配度对网络团购平台定价的影响。结论表明,平台需要对网络外部性较强、信誉较高且差异化程度较小的一方收取较低的交易费甚至免费,相反则抽取较高佣金,同时提高平台的搜索匹配概率将对企业利润产生显著的正向影响。网络团购平台需通过不断提高差异化程度和卖方信誉等方式,来吸引更多用户并达成更多交易量,从而使团购企业真正获得盈利。%In recent years,two-sided market theory has been a hot spot in the field of industrial organization.Combining with the characteristics of network group-buying platform,a pricing model suitable for the network group-buying platform is established,and the impacts of crossover network externalities,differentiation degree,the sellers＇ reputation and search efficiency are discussed.The conclusions show that platform needs to charge lower fee or even be free on the side which has stronger network externalities,higher reputation and differentiation degree,and on the contrary charges higher commissions.At the same time,improving the search matching probability will have a significantly positive impact on the corporate profit.Network group-buying platform needs to attract more users and achieve more deals to make the enterprise gain profit by means of improving differentiation degree,sellers＇ credit and so on.
谢健骊; 李翠然; 赵佳颖
2014-01-01
The paper presented a spectrum allocation algorithm for cognitive radio networks using the equilibri-um price theory.With the algorithm,the two-stage clustering spectrum allocation model was adopted and the expression of the optimal spectrum prices per unit for each stage was analyzed and deduced in consideration of the number of spectrum units,the number of cluster-heads and cluster-members,different priority levels of nodes and the number of active communications of nodes.Simulation results show as folliws:The proposed al-gorithm guarantees that the user (node)with the higher priority can obtain more spectrum resources in a cogni-tive radio network at the cost of the total spectrum revenue decreasing by less than 2%,as compared with the spectrum allocation strategy without taking the priority into consideration;also,it reflects the different spec-trum revenues of nodes of different priorities rationally.%提出一种基于均衡价格理论的认知无线网络频谱分配算法，此算法采用簇间、簇内两阶段的频谱分配方式，理论上分析并推导出不同阶段的最佳频谱单价与频谱数目、簇头及簇成员节点数、节点服务优先级别以及节点自身的通信活动次数之间的数学关系表达式。仿真结果表明：与无优先级的频谱分配方式相比，所提算法以降低不到2个百分点的频谱总收益为代价，可使认知无线网络中的高优先级用户(或节点)获得较多频谱，理性地体现出不同优先等级节点的频谱收益区别。
杨江涛; 孙春顺; 杨安; 刘佳
2016-01-01
为了进一步提高电力系统的可靠性和经济性，对配电网中储能设备的容量进行合理配置。基于分布式储能装置的引入给配电系统带来的影响，并考虑峰谷电价政策的影响，针对储能装置带来的经济效益分别从发电侧、输配电过程、降低网损、峰谷电价效益等各方面进行了经济性上的量化；结合储能装置的自身成本，以年收益最大为目标建立了储能装置容量的优化配置模型。最后考虑储能装置给系统潮流带来的影响，在约束条件中加入节点电压波动约束，通过对算例进行分析，得到了不同类型储能设备的最优容量配置。%In order to improve the reliability and economy of power system further, the capacity of energy storage device should be allocated with ration in the power distribution network. This paper analyzes the effect of the energy storage device on the power distribution system. On this basis, taking the influence of the peak valley price policy on the system into consideration, the benefits of the energy storage device to the system are analyzed, from the as-pects of the power generation, transmission and distribution process, network loss reduce, peak valley price benefit and so on, and are quantified on the side of economy. Combined with the costs of the energy storage device, with the goal of maximizing the revenue, an optimal allocation model of energy storage device capacity is established. Finally, considering the effects of energy storage device to the system trend and adding node voltage fluctuation in constraint conditions, the optimal capacity configurations of different types of energy storage devices are obtained by the analysis of the proposed example.
Complex network analysis of conventional and Islamic stock market in Indonesia
Rahmadhani, Andri; Purqon, Acep; Kim, Sehyun; Kim, Soo Yong
2015-09-01
The rising popularity of Islamic financial products in Indonesia has become a new interesting topic to be analyzed recently. We introduce a complex network analysis to compare conventional and Islamic stock market in Indonesia. Additionally, Random Matrix Theory (RMT) has been added as a part of reference to expand the analysis of the result. Both of them are based on the cross correlation matrix of logarithmic price returns. Closing price data, which is taken from June 2011 to July 2012, is used to construct logarithmic price returns. We also introduce the threshold value using winner-take-all approach to obtain scale-free property of the network. This means that the nodes of the network that has a cross correlation coefficient below the threshold value should not be connected with an edge. As a result, we obtain 0.5 as the threshold value for all of the stock market. From the RMT analysis, we found that there is only market wide effect on both stock market and no clustering effect has been found yet. From the network analysis, both of stock market networks are dominated by the mining sector. The length of time series of closing price data must be expanded to get more valuable results, even different behaviors of the system.
Price Recall, Bertrand Paradox and Price Dispersion With Elastic Demand
Carvalho, M.
2009-01-01
This paper studies the consequence of an imprecise recall of the price by the consumers in the Bertrand price competition model for a homogeneous good. It is shown that firms can exploit this weakness and charge prices above the competitive price. This markup increases for rougher recall of the pric
National Oceanic and Atmospheric Administration, Department of Commerce — Real-time price data collected by the Boston Market News Reporter. The NOAA Fisheries' "Fishery Market News" began operations in New York City on February 14, 1938....
National Oceanic and Atmospheric Administration, Department of Commerce — Standard prices are generated for cost recovery programs in the Individual Fishing Quota (IFQ) halibut and sablefish, BSAI Rationalized crab, and Central Gulf of...
Fischer, Richard B.
1986-01-01
Defines key terms and discusses things to consider when setting fees for a continuing education program. These include (1) the organization's philosophy and mission, (2) certain key variables, (3) pricing strategy options, and (4) the test of reasonableness. (CH)
Regulation of Pharmaceutical Prices
Kaiser, Ulrich; Méndez, Susan J.; Rønde, Thomas;
drugs, generics, and parallel imports with health care expenditures and producer revenues decreasing and co-payments increasing most for branded drugs. The reform also induced consumers to substitute from branded drugs – for which they have strong preferences – to generics and parallel imports......Reference prices constitute a main determinant of patient health care reimbursement in many countries. We study the effects of a change from an "external" (based on a basket of prices in other countries) to an "internal" (based on comparable domestic products) reference price system. We find...... that while our estimated consumer compensating variation is small, the reform led to substantial reductions in list and reference prices as well as co-payments, and to sizeable decreases in overall producer revenues, health care expenditures, and co-payments. These effects differ markedly between branded...
Regulation of Pharmaceutical Prices
Kaiser, Ulrich; Méndez, Susan J.; Rønde, Thomas;
2014-01-01
drugs, generics, and parallel imports with health care expenditures and producer revenues decreasing and co-payments increasing most for branded drugs. The reform also induced consumers to substitute from branded drugs – for which they have strong preferences – to generics and parallel imports......Reference prices constitute a main determinant of patient health care reimbursement in many countries. We study the effects of a change from an "external" (based on a basket of prices in other countries) to an "internal" (based on comparable domestic products) reference price system. We find...... that while our estimated consumer compensating variation is small, the reform led to substantial reductions in list and reference prices as well as co-payments, and to sizeable decreases in overall producer revenues, health care expenditures, and co-payments. These effects differ markedly between branded...
X.Q. Xu; C.S. Chang
2007-01-01
@@ The plasma edge includes the pedestal, scrape-off, and divertor regions. A complete edge physics should deal with the plasma, atomic, and the plasma-wall interaction phenomena. The edge provides the source of plasma through ionization of the incoming neutral particles and source of impurity through the wall sputtering. Edge plasma sets a boundary condition for the core confinement physics. Importance of the edge plasma has been elevated to the top list of the ITER physics research needs due to the necessity of the self-organized plasma pedestal and its destruction by edge localized mode activities. Extrapolation of the present tokamak data base predicts that a sufficient pedestal height is a necessary condition for the success of ITER.
VĂDUVA MARIA
2014-08-01
Full Text Available Studying the consumer’s behavior by the ordinal approach of utility with the help of indifference curves allows us to deduce the two “movement laws of demand” in this chapter: the demand for a “normal” good is decreasing function of its price and an increasing function of income. We will use the elasticity concept to measure the intensity of the relation that is established between the demand, on the one hand, and prices or income, on the other hand: elasticity – price, direct and crossed, and elasticity – income. We can classify the goods in many categories, depending on the values that this elasticity takes. The demand elasticity can be determined depending on price and income. It reflects the proportion in which the demand for different products changes with the modification of the consumers’ income, the other factors remaining constant. The elasticity compared to the income is a demonstration of legality from the consumer’s sphere, which determines a certain hierarchy of the needs of each population category in a certain level of income. The movement of prices orients both the options and decisions of producers, namely the most useful productions and the most efficient investments, as well as the consumers’ options and decisions on the most advantageous buying of goods and services that they need. The prices appear as a “signal system” coordinating and making coherence the economic agents’ decisions – producers, consumers and population.
Bocquet, L
2006-01-01
We show that the baking of potato wedges constitutes a crunchy example of edge effects, which are usually demonstrated in electrostatics. A simple model of the diffusive transport of water vapor around the potato wedges shows that the water vapor flux diverges at the sharp edges in analogy with its electrostatic counterpart. This increased evaporation at the edges leads to the crispy taste of these parts of the potatoes.
Bocquet, Lydéric
2007-02-01
We show that the baking of potato wedges constitutes a crunchy example of edge effects, which are usually demonstrated in electrostatics. A simple model of the diffusive transport of water vapor around the potato wedges shows that the water vapor flux diverges at the sharp edges in analogy with its electrostatic counterpart. This increased evaporation at the edges leads to the crispy taste of these parts of the potatoes.
Are Fuel Price Hikes Justifiable?
2009-01-01
China saw its third fuel price hike this year when the National Development and Reform Commission, China’s top price regulator, hiked gasoline and diesel retail prices up by 9 percent, effective on June 30. It is the second rally in a month after the country initiated a new fuel pricing scheme in May.
Relative Prices and Inflation Stabilisation
Aoki, Kosuke
2015-01-01
When price adjustment is sluggish, inflation is costly in terms of welfare because it distorts various kinds of relative prices. Stabilising aggregate price inflation does not necessarily minimise these costs, but stabilising a well-designed core inflation minimises the cost of relative price fluctuations and thus the cost of inflation.
Equilibrium adjustment of disequilibrium prices
Herings, P.J.J.; van der Laan, G.; Talman, A.J.J.; Venniker, R.
1994-01-01
We consider an exchange economy in which price rigidities are present. In the short run the non-numeraire commodities have a exible price level with respect to the numeraire commodity but their relative prices are mutually fixed. In the long run prices are assumed to be completely exible. For a give
Cognitive Network Spectrum Sharing Game Theory Model Based on Price%基于价格的认知网络频谱共享博弈论模型
黄德文; 周井泉
2013-01-01
As the wireless mobile terminal and new radio application business has been rapid development,people use the radio spectrum more frequently and the wireless spectrum resource demand is increasing,so that the wireless spectrum becomes a scarce resource,which will become the bottleneck of the development of wireless communication. In order to use spectrum resources more efficiently,use the classical economics of Cournot game model to analyze the spectrum allocation in cognitive radio networks,considering the influence of main ( authorized) user spectrum supply to the price of spectrum's,the original price function was improved,reflecting main users' in-fluence to the price of spectrum. Constructed a new spectrum allocation model,proposing a new utility function,to better analyse cognitive radio spectrum allocation,and demonstrate the existence of the Nash Equilibrium,effectively improving the spectrum utilization rate. The simulation results show that,this algorithm is more close to the actual network,better reflecting the main users of the bidding intention, have some practical application ability.%随着各种无线移动终端和各种无线电新应用业务得到飞速发展，人们对无线频谱的使用更加频繁，对无线频谱资源的需求日益增加，从而使无线频谱成为一种稀缺资源。频谱的稀缺会成为制约无线通信行业发展的瓶颈。为了更加有效地利用频谱资源，文中利用经典的经济学中的古诺博弈模型来分析认知网络中的频谱分配问题，考虑主要(授权)用户频谱供给量对频谱价格的影响，对原有价格函数进行改进，体现主要用户对频谱价格的影响，构建新的频谱分配模型，并提出新的效用函数，来更好地分析认知无线电网络中频谱分配问题，证明纳什均衡的存在性，有效提高频谱利用率。仿真结果表明，该算法更加贴近实际网络，更好地反应了主要用户的竞价意愿，达到
Arndt, Channing; Benfica, Rui; Maximiano, Nelson
2008-01-01
Rising world prices for fuel and food represent a negative terms-of-trade shock for Mozambique. The impacts of these price rises are analyzed using various approaches. Detailed price data show that the world price increases are being transmitted to domestic prices. Short-run net benefit ratio...... of Mozambique indicates that the fuel price shock dominates rising food prices from both macroeconomic and poverty perspectives. Again, negative impacts are larger in urban areas. The importance of agricultural production response in general and export response in particular is highlighted. Policy analysis...
High Drug Prices Hurt Everyone
Halpenny, Genevieve M.
2016-01-01
Turing Pharmaceuticals raised the price of Daraprim 5,500%, illustrating how the absence of competition in the sale of low-volume, low-price drugs can lead to price gouging. For patented medicines, society allows supracompetitive pricing to incentivize innovation. However, Gilead���s decision to sell Sovaldi for $84,000 per course of treatment raised the question whether society must accept any price set by the patent holder. Unfortunately, these incidents illustrate a br...
Fuel Price Effects on Readiness
2014-05-01
31 B. Measuring the Response to Changes in Fuel Prices across Budget Years: Long- term Price Elasticity ...Changes in Fuel Prices across Budget Years: Long-term Price Elasticity In order to determine the responsiveness of inter-year OPTEMPO to inter-year... elasticity of OPTEMPO (our readiness measure) with respect to price . 0 1,000 2,000 3,000 4,000 33 1. Army Analysis In order to avoid overlooking
Support vector machine for day ahead electricity price forecasting
Razak, Intan Azmira binti Wan Abdul; Abidin, Izham bin Zainal; Siah, Yap Keem; Rahman, Titik Khawa binti Abdul; Lada, M. Y.; Ramani, Anis Niza binti; Nasir, M. N. M.; Ahmad, Arfah binti
2015-05-01
Electricity price forecasting has become an important part of power system operation and planning. In a pool- based electric energy market, producers submit selling bids consisting in energy blocks and their corresponding minimum selling prices to the market operator. Meanwhile, consumers submit buying bids consisting in energy blocks and their corresponding maximum buying prices to the market operator. Hence, both producers and consumers use day ahead price forecasts to derive their respective bidding strategies to the electricity market yet reduce the cost of electricity. However, forecasting electricity prices is a complex task because price series is a non-stationary and highly volatile series. Many factors cause for price spikes such as volatility in load and fuel price as well as power import to and export from outside the market through long term contract. This paper introduces an approach of machine learning algorithm for day ahead electricity price forecasting with Least Square Support Vector Machine (LS-SVM). Previous day data of Hourly Ontario Electricity Price (HOEP), generation's price and demand from Ontario power market are used as the inputs for training data. The simulation is held using LSSVMlab in Matlab with the training and testing data of 2004. SVM that widely used for classification and regression has great generalization ability with structured risk minimization principle rather than empirical risk minimization. Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. The mean absolute percentage error (MAPE) for the proposed model shows that SVM performs well compared to neural network.
7 CFR 1001.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1001.50 Section 1001.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
7 CFR 1032.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1032.50 Section 1032.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
7 CFR 1033.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1033.50 Section 1033.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
7 CFR 1006.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1006.50 Section 1006.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
7 CFR 1005.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1005.50 Section 1005.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
7 CFR 1007.50 - Class prices, component prices, and advanced pricing factors.
2010-01-01
... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1007.50 Section 1007.50 Agriculture Regulations of the Department of Agriculture (Continued..., and advanced pricing factors. See § 1000.50....
Baker, W; Marn, M; Zawada, C
2001-02-01
Companies generally have set prices on the Internet in two ways. Many start-ups have offered untenably low prices in a rush to capture first-mover advantage. Many incumbents have simply charged the same prices on-line as they do off-line. Either way, companies are missing a big opportunity. The fundamental value of the Internet lies not in lowering prices or making them consistent but in optimizing them. After all, if it's easy for customers to compare prices on the Internet, it's also easy for companies to track customers' behavior and adjust prices accordingly. The Net lets companies optimize prices in three ways. First, it lets them set and announce prices with greater precision. Different prices can be tested easily, and customers' responses can be collected instantly. Companies can set the most profitable prices, and they can tap into previously hidden customer demand. Second, because it's so easy to change prices on the Internet, companies can adjust prices in response to even small fluctuations in market conditions, customer demand, or competitors' behavior. Third, companies can use the clickstream data and purchase histories that it collects through the Internet to segment customers quickly. Then it can offer segment-specific prices or promotions immediately. By taking full advantage of the unique possibilities afforded by the Internet to set prices with precision, adapt to changing circumstances quickly, and segment customers accurately, companies can get their pricing right. It's one of the ultimate drivers of e-business success.
1984-08-01
T. 0. "On boundary detection." A. I. Memo 183, MIT, 1980. Hildreth, E. C. "Implementation of a theory of edge detection ." A. /. Memo 579, MIT, 1980...Detection." IEEE Trans. PAMI, 6, 678-680, 1983. Marr, 0. C. and Hildreth, E. C, " Theory of edge detection ." Proc. R. Soc. Lond. B, 207, 187-217, 1980. Marr
Logistics: Price Rises Incurred by High Oil Price
Lai Zhihui
2011-01-01
@@ "When the oil price grows by 100%, the logistic indus-try will see a price growth of 40%, while the logistics in-dustry a price rise of 35%, which means every price increase of 5% in the oil price will bring along that of 2% in this industry." said Liu Zongsheng, General Manager of Itochu Logistics Co., Ltd., on the seminar "Focusing on the eco-nomic consequences of raising oil price, interest rate and deposit reserve ratio", which was held recently.
Samuelson, Paul A.
1971-01-01
Because a commodity like wheat can be carried forward from one period to the next, speculative arbitrage serves to link its prices at different points of time. Since, however, the size of the harvest depends on complicated probability processes impossible to forecast with certainty, the minimal model for understanding market behavior must involve stochastic processes. The present study, on the basis of the axiom that it is the expected rather than the known-for-certain prices which enter into all arbitrage relations and carryover decisions, determines the behavior of price as the solution to a stochastic-dynamic-programming problem. The resulting stationary time series possesses an ergodic state and normative properties like those often observed for real-world bourses. PMID:16591903
JESSY ZHANG
2006-01-01
@@ Viessmann Werke, a German-based global manufacturer of heating technology products, settled down in an industrial development zone in Beijing suburb in 2001. In recent years, however, they have witnessed a price increase for land use in their development zone and nearby areas. "There will be more infrastructure construction in this area and a new exhibition center is said to be built here," says Dr. Andreas Tank, executive manager of Viessmann Werke. "We see the demand for land is increasing and newcomers must pay higher prices for land use than we paid. "Viessmann has fixed its expenditure on land use fees by signing a long-term contract with the development zone.
Pricing Volatility Referenced Assets
Alan De Genaro Dario
2006-12-01
Full Text Available Volatility swaps are contingent claims on future realized volatility. Variance swaps are similar instruments on future realized variance, the square of future realized volatility. Unlike a plain vanilla option, whose volatility exposure is contaminated by its asset price dependence, volatility and variance swaps provide a pure exposure to volatility alone. This article discusses the risk-neutral valuation of volatility and variance swaps based on the framework outlined in the Heston (1993 stochastic volatility model. Additionally, the Heston (1993 model is calibrated for foreign currency options traded at BMF and its parameters are used to price swaps on volatility and variance of the BRL / USD exchange rate.
IS THE PRICE RIGHT? PRICING FOR LONG TERM PROFITABILITY
Andrea Erika NYÁRÁDI
2007-01-01
Full Text Available The way how we choose our pricing strategy has a significant impact on company’s success. Nowadays companies more and more adopt a new way of thinking in pricing, namely pricing for a long term period in order to bring higher profitability, to build an efficient pricing strategy. Marketers have only recently begun to focus seriously on effective pricing. These companies are the so called progressive companies. They have begun doing more than just worrying about pricing. To increase profitability many are abandoning traditional reactive pricing procedures in favor of proactive pricing, making explicit corporate decisions to change their focus to growth in top-line sales to growth in profitability. The long-term implications of price strategies are still under-researched, and managers should be aware of shifts in customer reactions that may result from frequent adoption of certain strategies. The company pricing strategy should be seen in relation to developments in the company variables, internal ones (capital strength, competencies, organizational conditions, efficiency of the work force etc. as well as external ones (customers, competitors, the technological development etc., adopting strategic pricing. In this paper I will present the most effective pricing strategies leading to long term profitability, and also suggest practical conditions for pricing strategies to maximize profit in the long run.
Gies, H; Gies, Holger; Klingmuller, Klaus
2006-01-01
We compute Casimir forces in open geometries with edges, involving parallel as well as perpendicular semi-infinite plates. We focus on Casimir configurations which are governed by a unique dimensional scaling law with a universal coefficient. With the aid of worldline numerics, we determine this coefficient for various geometries for the case of scalar-field fluctuations with Dirichlet boundary conditions. Our results facilitate an estimate of the systematic error induced by the edges of finite plates, for instance, in a standard parallel-plate experiment. The Casimir edge effects for this case can be reformulated as an increase of the effective area of the configuration.
Labrecque, Joseph
2012-01-01
Adobe Edge Quickstart Guide is a practical guide on creating engaging content for the Web with Adobe's newest HTML5 tool. By taking a chapter-by-chapter look at each major aspect of Adobe Edge, the book lets you digest the available features in small, easily understandable chunks, allowing you to start using Adobe Edge for your web design needs immediately. If you are interested in creating engaging motion and interactive compositions using web standards with professional tooling, then this book is for you. Those with a background in Flash Professional wanting to get started quickly with Adobe
ANTESEDEN DAN KONSEKUENSI DARI PRICE SATISFACTION
Steven Dharma; Asep Hermawan
2012-01-01
The purpose of this paper is to explore the antecedents and consequents of price satisfaction. It argues that price satisfaction is composed of several dimensions (price transparency, pricequality ratio, relative price, price confidence, price reliability, and price fairness) and that companies should consider these dimensions when monitoring customer price satisfaction. Based on a theoretical discussion of the price dimensions, a questionnaire is developed that measures customer satisfact...
Do Flexible Durable Goods Prices Undermine Sticky Price Models?
Robert Barsky; Christopher L. House; Miles Kimball
2003-01-01
Multi-sector sticky price models have surprising implications when durable goods have flexible prices. While in actual data the production of virtually all durables exhibits strong negative responses to monetary contractions, in dynamic general equilibrium models a monetary contraction causes the output of flexibly priced durables to expand. Indeed, in the polar case in which only nondurables have sticky prices, the negative comovement of durable and nondurable production exactly offsets and ...
On Storekeepers' Pricing Behavior.
B. Bode (Ben); J. Koerts (Johan); A.R. Thurik (Roy)
1986-01-01
textabstractThis research note deals with a quantitative analysis of differences in percentage gross margin between individual stores in the retail trade. A number of hypotheses on pricing behavior of storekeepers are tested using Dutch survey data from nine different types of retail stores. We defi
Bork, Lasse; Møller, Stig Vinther
2012-01-01
We examine US housing price forecastability using a common factor approach based on a large panel of 122 economic time series. We …nd that a simple three-factor model generates an explanatory power of about 50% in one-quarter ahead in-sample forecasting regressions. The predictive power of the mo...
Jensen, Dennis Ramsdahl
Konferencebidraget indeholder en kritisk analyse af transfer pricing reglerne på henholdsvis moms og indkomstskatterettens område med henblik på en diskussion af, det er hensigtsmæssigt med en harmonisering af reglerne på tværs af de to retsområder...
Read, Simon
1989-01-01
Describes a game that illustrates the effects of pricing on profit. Students compete against each other in an imaginary industry and become familiar with decision-making processes. Depicts the gameboard, how to make it, and how to use it. (GG)
On Storekeepers' Pricing Behavior.
B. Bode (Ben); J. Koerts (Johan); A.R. Thurik (Roy)
1986-01-01
textabstractThis research note deals with a quantitative analysis of differences in percentage gross margin between individual stores in the retail trade. A number of hypotheses on pricing behavior of storekeepers are tested using Dutch survey data from nine different types of retail stores. We
无
2005-01-01
Continuous cold RE market has been a headache for producers. Markup of raw materials, energy and transportation expense is a disaster in succession. Entering March, there is a trend of warm-up in the market, and some RE products have got higher prices than last year. Details are listed below.
Road pricing with complications
Fosgerau, Mogens; Van Dender, Kurt
2013-01-01
, and a highly stylised model of congestion is used. The simple analysis also ignores that real pricing schemes are only rough approximations to ideal systems and that inefficiencies in related markets potentially affect the case for congestion charges. The canonical model tends to understate the marginal...
Penasse, J.N.G.; Renneboog, L.D.R.; Spaenjers, C.
2014-01-01
We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants’ confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns.
无
2005-01-01
Recently, price of terbia soars to RMB $2600/ nearly changing by day. It is estimated that it will climt RMB$3000/Kg or so. Rising of terbia is mainly driven following factors: 1. Reduced Raw Materials High terbium contained Longnan ore in Ganzhou completely stopped leaching, which will result in the sh
Faruqui, Ahmad
2006-10-15
The author uses the Rip Van Winkle approach favored by marketers to gaze, clear-eyed, into the future - say, the year 2050 - to visualize alternative demand-response possibilities. Dare we go California Dreamin' of a distant utopia - or is it inevitable that pricing myopia will keep us from attaining the fulfillment of many of our career goals? (author)
Jensen, Dennis Ramsdahl
Konferencebidraget indeholder en kritisk analyse af transfer pricing reglerne på henholdsvis moms og indkomstskatterettens område med henblik på en diskussion af, det er hensigtsmæssigt med en harmonisering af reglerne på tværs af de to retsområder...
Optimal pricing and investment in the electricity sector in Tamil Nadu, India
Murthy, Ranganath Srinivas
2001-07-01
Faulty pricing policies and inadequate investment in the power sector are responsible for the chronic power shortages that plague Tamil Nadu and the rest of India. Formulae for optimal pricing rules are derived for a social welfare maximizing Electricity Board which sells electricity that is used both as an intermediate, and as a final good. Because of distributional constraints, the optimal prices deviate systematically from marginal costs. Optimal relative price-marginal cost differentials are computed for Tamil Nadu, and are found to indicate a lower degree of subsidization than the prevailing prices. The rationalization of electricity tariffs would very likely increase the Board's revenues. The cost-effectiveness of nuclear power in India is examined by comparing actual data for the Madras Atomic Power Project and the Singrauli coal-fired thermal power station. The conventional (non-environmental) costs of power generation are compared at both market prices and shadow prices, calculated according to the UNIDO guidelines for project evaluation. Despite favorable assumptions for the costs of the nuclear plant, coal had a decided edge over nuclear in Tamil Nadu. Remarkably, the edge varied little when market prices are replaced by shadow prices in the computations. With regard to the environmental costs, far too much remains unknown. More research is therefore needed on the environmental impacts of both types of power generation before a final choice can be made.
Geloni, Gianluca; Saldin, Evgeni; Schneidmiller, Evgeni; Yurkov, Mikhail
2008-01-01
We formulate a complete theory of Edge Radiation based on a novel method relying on Fourier Optics techniques. Similar types of radiation like Transition Undulator Radiation are addressed in the framework of the same formalism. Special attention is payed in discussing the validity of approximations upon which the theory is built. Our study makes consistent use of both similarity techniques and comparisons with numerical results from simulation. We discuss both near and far zone. Physical understanding of many asymptotes is discussed. Based on the solution of the field equation with a tensor Green's function technique, we also discuss an analytical model to describe the presence of a vacuum chamber. In particular, explicit calculations for a circular vacuum chamber are reported. Finally, we consider the use of Edge Radiation as a tool for electron beam diagnostics. We discuss Coherent Edge Radiation, Extraction of Edge Radiation by a mirror, and other issues becoming important at high electron energy and long ...
Grover, Chris
2011-01-01
Want to use an Adobe tool to design animated web graphics that work on iPhone and iPad? You've come to the right book. Adobe Edge Preview 3: The Missing Manual shows you how to build HTML5 graphics using simple visual tools. No programming experience? No problem. Adobe Edge writes the underlying code for you. With this eBook, you'll be designing great-looking web elements in no time. Get to know the workspace. Learn how Adobe Edge Preview 3 performs its magic.Create and import graphics. Make drawings with Edge's tools, or use art you designed in other programs.Work with text. Build menus, lab
Pricing Data: A Look at Past Proposals, Current Plans, and Future Trends
Sen, Soumya; Ha, Sangtae; Chiang, Mung
2012-01-01
Traditionally, network operators have only used simple flat-rate unlimited data plans to vie for customers. But today, with the popularity of mobile devices and exponential growth of apps, videos, and clouds, service providers are gradually moving towards more sophisticated pricing schemes, including dynamic pricing. This decade will therefore likely witness a major shift in network pricing schemes. However, there are several unique challenges with the dynamic pricing of mobile data, including new system requirements and social adoption. This paper reviews some of the well known past pricing proposals (both static and dynamic), their current realization in various data plans, and new research directions. Unlike a traditional survey, this work is an attempt to explore benefits and challenges of pricing plans that are currently being used by ISPs in different parts of the world so as to facilitate the networking community's efforts in recognizing trends and shaping an appropriate research agenda.
A multilayer approach for price dynamics in financial markets
Biondo, Alessio Emanuele; Rapisarda, Andrea
2016-01-01
We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dy- namics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.
Decomposition of Market Clearing Price in Electricity Markets
Wachi, Tsunehisa; Fukutome, Suguru; Chen, Luonan; Makino, Yoshinori
This paper aims to develop a novel methodology to decompose MCP (market clearing price) in a single price auction market with AC transmission network. Specifically, we first formulate the auction market as a nonlinear optimization problem, and then propose an algorithm to decompose MCP into various factors, such as bidding curves, generations, transmission congestion, voltage limitations and other constraints. Several numerical simulations have been used to demonstrate the effectiveness of our approach.
Weighting links based on edge centrality for community detection
Sun, Peng Gang
2014-01-01
Link weights have the equally important position as links in complex networks, and they are closely associated with each other for the emergence of communities. How to assign link weights to make a clear distinction between internal links of communities and external links connecting communities is of vital importance for community detection. Edge centralities provide a powerful approach for distinguishing internal links from external ones. Here, we first use edge centralities such as betweenness, information centrality and edge clustering coefficient to weight links of networks respectively to transform unweighted networks into weighted ones, and then a weighted function that both considers links and link weights is adopted on the weighted networks for community detection. We evaluate the performance of our approach on random networks as well as real-world networks. Better results are achieved on weighted networks with stronger weights of internal links of communities, and the results on unweighted networks outperform that of weighted networks with weaker weights of internal links of communities. The availability of our findings is also well-supported by the study of Granovetter that the weak links maintain the global integrity of the network while the strong links maintain the communities. Especially in the Karate club network, all the nodes are correctly classified when we weight links by edge betweenness. The results also give us a more comprehensive understanding on the correlation between links and link weights for community detection.
Arndt, Channing; Benfica, Rui; Maximiano, Nelson;
2008-01-01
Rising world prices for fuel and food represent a negative terms-of-trade shock for Mozambique. The impacts of these price rises are analyzed using various approaches. Detailed price data show that the world price increases are being transmitted to domestic prices. Short-run net benefit ratio...... analysis indicates that urban households and households in the southern region are more vulnerable to food price increases. Rural households, particularly in the North and Center, often benefit from being in a net seller position. Longer-term analysis using a computable general equilibrium (CGE) model...... of Mozambique indicates that the fuel price shock dominates rising food prices from both macroeconomic and poverty perspectives. Again, negative impacts are larger in urban areas. The importance of agricultural production response in general and export response in particular is highlighted. Policy analysis...
2007-01-01
The National Development and Reform Commission(NDRC),China’s top economic planner,announced at the end of October that the benchmark prices of gasoline,diesel oil and aviation kerosene would be raised by 500 yuan per ton. Recently,international oil prices have been rising continuously.Crude oil futures prices traded in New York surged to＄93 per barrel on October 29. However,in China,oil prices are set by the government and not by the market. The recent hike on the price of oil in China is a measure implemented,to narrow the gap between soaring global crude oil prices and domestic fuel prices.NDRC officials answered questions posed by Xinhua News Agency about recent oil price hikes.The questions and answers follow:
Price knowledge during grocery shopping
Jensen, Birger Boutrup; Grunert, Klaus G
2014-01-01
Past research on consumer price knowledge has varied considerably partly due to differences in how and when price knowledge is measured.This paper applies a multi-point, multi-measure approach to reconcile differences in past price knowledge research by examining systematicrelationships between...... accessible at the store exit. These findings enable the authors to reconcile diverging results from past research,showing how consumer price knowledge evolves and suggesting that the vast majority of consumers learn about prices, whether consciously orunconsciously, during grocery shopping. Thus, when...... applying a multi-point, multi-measure approach, consumers appear to know more aboutprices than suggested by past research. Determinants of price knowledge are also examined and the results indicate that price knowledge buildsup not only because of active search but also due to accidental exposure to prices...
Leandro dos Santos Coelho
2007-04-01
Full Text Available As ferramentas de identificação de sistemas e previsão de séries temporais permitem a concepção de modelos matemáticos baseados em dados numéricos. O problema essencial, nestes casos, é determinar o modelo matemático apropriado. Esse artigo apresenta o projeto de uma rede neural função de base radial (RN-RBF para a previsão de séries temporais. Na utilização da RN-RBF para previsão de sistemas não-lineares é difícil determinar um conjunto apropriado de centros e aberturas para as funções de ativação Gaussianas para obter uma boa estrutura. Neste trabalho, a configuração da RN-RBF é baseada em uma abordagem híbrida baseada em método de agrupamento de dados de Gustafson-Kessel e procedimento de otimização usando evolução diferencial. O projeto de RN-RBF é validado para previsão de um passo à frente dos preços de troncos de eucalipto para celulose e serraria para ilustrar a eficiência da abordagem híbrida proposta. Além disso, o desempenho do projeto de RN-RBF baseado nos resultados de previsão é apresentado e discutido neste artigo.Computational tools of system identification and prediction of time series allows for the conception of mathematical models based on numerical data. The key problem in these cases is to find a suitable mathematical model. This paper presents a radial basis function neural network (RBF-NN design for forecasting time series. Using the RBF-NN for nonlinear system forecasting is quite difficult as one has to choose an appropriate set of centers and spreads for the Gaussian activation functions to achieve a good network structure. In this work, the setup of RBF-NN is based on a hybrid method based on the Gustafson-Kessel clustering method and optimization procedure by differential evolution. The RBF-NN design is validated for the one-step ahead forecasting of eucalyptus wood prices for cellulose and sawmill to illustrate the effectiveness of this hybrid approach. The performance of
Model Penentuan Harga ( Price ) Dinamis
Laili, Erna
2012-01-01
Information about the demand curve is not available enough practically, those sellers face some constrains to get the optimal revenue. The seller’s revenue is influenced by the dynamic pricing caused by price sensitivity and the uncertainty available marketing share. The thesis aims to create mathematical model for determining the dynamic pricing by learning both properties determination model and dynamic pricing factors. The results of the research shows that for two parameter...
Azar, Jose
2009-01-01
This paper studies the joint dynamics of oil prices and interest in electric cars, measured as the volume of Google searches for related phrases. Not surprisingly, I find that oil price shocks predict increases in Google searches for electric cars. Much more surprisingly, I also find that an increase in Google searches predicts declines in oil prices. The high level of public interest in electric cars between April and August of 2008 can explain approximately half of the decline in oil prices...
Developing a consumer pricing strategy.
Sturm, Arthur; Tiedemann, Frank
2013-05-01
Healthcare providers can learn a variety of pricing lessons from the retail market: For providers, wholesale pricing--"the price to play"--alone is not enough. Once a hospital or health system chooses a market position, the provider creates an expectation that must be met-consistently. Consumer loyalty is fluid, and the price of care or service is not always the motivator for choosing one organization over another; intangibles such as location and level of customer service also drive purchasing decisions.
Brand the Pricing: Critical Critique
Alam Kazmi, Syed Hasnain
2015-01-01
Brand pricing decision models and established theories in the marketing and econometrics focus typically on assuming the symmetric competing businesses. The empirical generalities are key for strategic marketplace planning. The significance of pricing to customer store and brand choices are always regarded as a widely known truth among marketing scholars and explains consumer’s role responding to their psychological representations of price rather than price itself. Scholars have ...
Price Regulations in a Multi-unit Uniform Price Auction
Boom, Anette
not exceed the price cap whereas a selective bid cap for only the larger firms, does not guarantee this outcome. A sufficiently high bid floor always destroys pure strategy equilibria with equilibrium prices above the marginal costs, no matter whether the floor applies to all or only to relatively small......Inspired by recent regulations in the New York ICAP market we examine the effect of different price regulations on a multi-unit uniform price auction. We investigate a bid cap and a bid foor. Given suffciently high total capacities general bid caps always ensure that the market price does...
Price Regulations in a Multi-unit Uniform Price Auction
Boom, Anette
Inspired by recent regulations in the New York ICAP market we examine the effect of different price regulations on a multi-unit uniform price auction. We investigate a bid cap and a bid foor. Given suffciently high total capacities general bid caps always ensure that the market price does...... not exceed the price cap whereas a selective bid cap for only the larger firms, does not guarantee this outcome. A sufficiently high bid floor always destroys pure strategy equilibria with equilibrium prices above the marginal costs, no matter whether the floor applies to all or only to relatively small...
Thinking strategically about electricity pricing
Toulson, D. (Barakat and Chamberlin, Inc., Oakland, CA (United States))
1992-12-01
This report describes an approach by which utilities can view pricing from a strategic, market-oriented perspective. It begins by reviewing pricing practices found in private industry and develops a framework for utility rate design that incorporates both customer value and cost of service. A market intelligence system for gathering data relevant to pricing decisions is also briefly outlined.
The Pricing of Economics Books.
Laband, David; Hudson, John
2003-01-01
Examines the pricing and other characteristics of books. Notes substantial increases in book prices between 2000 and 1985 data. Suggests a major factor is the increasing importance of foreign presses that sell books at higher prices. Indicates that discount on paperbacks appear to have been relatively stable in the two years studied. (JEH)
Price Discrimination: A Classroom Experiment
Aguiló, Paula; Sard, Maria; Tugores, Maria
2016-01-01
In this article, the authors describe a classroom experiment aimed at familiarizing students with different types of price discrimination (first-, second-, and third-degree price discrimination). During the experiment, the students were asked to decide what tariffs to set as monopolists for each of the price discrimination scenarios under…
RESTAURANT NO. 2: PRICE INCREASES
2003-01-01
'DSR', the concession holder of Restaurant no. 2 (bldg. 504 - Meyrin site), has submitted to the Restaurant Supervisory Committee a request to increase certain prices. After close examination, the Committee has established that the proposed increases are compatible with the relevant price indexing mechanisms and other contractual conditions. The new prices will apply as from Monday, June 30, 2003.
RESTAURANT NO. 3: PRICE INCREASES
2003-01-01
'AVENANCE', the concession holder of Restaurant no. 3 (bldg. 866 - Prévessin site), has submitted to the Restaurant Supervisory Committee a request to increase its prices. After close examination, the Committee has established that the proposed increases are compatible with the relevant price indexing mechanisms and other contractual conditions. The new prices will apply as from Monday, June 2, 2003.
2009-01-01
China adheres to a more flexible oil pricing mechanismBy ordering a hefty 9-percent price increase in gasoline and diesel, China is lending credibility to its pledges of a more market-oriented pricing system. The decision, announced by the National Development and Reform Commission
1982-03-01
Price increases in the Jamaica CSM program went into effect on August 31, 1981. The program began in 1975. While the need for higher prices has been under discussion for the past 3 years, this is the 1st time the requisite approval from the Jamaica Price Commission has been obtained. The Jamaica National Family Planning Board (JNFPB) reports that the Panther 3-pack (condom) is up US$0.15 to US$0.30. Each Perle package (oral contraceptive) was increased by US$0.20. Single cycle Perle now sells for US$0.50, and 3-pack Perle sells for US$1.10. The 6-year price stagnation experienced by the CSM program resulted in a decreasing operational budget as program costs continued to rise. Marketing costs alone during this period escalated by 100-300%. For example, Panther pop-up display cartons cost the project US 16U each in 1975. By 1979 the same product cost US 49U. Newspaper advertisements have increased from the 1975 cost of US$68.00 to nearly $200.00 per placement. The overall inflation rate in Jamaica during the last 5 years has averaged more than 20% annually. In the face of these rising costs, outlet expansion for Perle has been prevented, wholesaler margins have been unavailable, and new retailer training has been discontinued. It is projected that the new prices will result in an annual increased revenues of US$80,000 which will be used to reinstate these essential marketing activities. The JNFPB is also planning to introduce a Panther 12-pack and Panther strips to the CSM product line. According to Marketing Manager Aston Evans, "We believe the public is now ready for this type of packaging" which is scheduled to be available soon. Panther is presently only available in a 3-pack, but annual sales have been steady. The new 12-pack will be stocked on supermarket shelves to provide higher product visibility and wider distribution. The selling price has been set as US$1.20 and is expected to yield a 25% increase in sales during the 1st year. A complete sales promotion
Patients' views on price shopping and price transparency.
Semigran, Hannah L; Gourevitch, Rebecca; Sinaiko, Anna D; Cowling, David; Mehrotra, Ateev
2017-06-01
Driven by the growth of high deductibles and price transparency initiatives, patients are being encouraged to search for prices before seeking care, yet few do so. To understand why this is the case, we interviewed individuals who were offered access to a widely used price transparency website through their employer. Qualitative interviews. We interviewed individuals enrolled in a preferred provider organization product through their health plan about their experience using the price transparency tool (if they had done so), their past medical experiences, and their opinions on shopping for care. All interviews were transcribed and manually coded using a thematic coding guide. In general, respondents expressed frustration with healthcare costs and had a positive opinion of the idea of price shopping in theory, but 2 sets of barriers limited their ability to do so in reality. The first was the salience of searching for price information. For example, respondents recognized that due to their health plan benefits design, they would not save money by switching to a lower-cost provider. Second, other factors were more important than price for respondents when choosing a provider, including quality and loyalty to current providers. We found a disconnect between respondents' enthusiasm for price shopping and their reported use of a price transparency tool to shop for care. However, many did find the tool useful for other purposes, including checking their claims history. Addressing the barriers to price shopping identified by respondents can help inform ongoing and future price transparency initiatives.
Agosta, Roxana; Bilbija, Dushan; Deutsch, Marc; Gallant, David; Rose, Don; Shreve, Gene; Smario, David; Suffredini, Brian
1992-01-01
As intercontinental business and tourism volumes continue their rapid expansion, the need to reduce travel times becomes increasingly acute. The Edge Supersonic Transport Aircraft is designed to meet this demand by the year 2015. With a maximum range of 5750 nm, a payload of 294 passengers and a cruising speed of M = 2.4, The Edge will cut current international flight durations in half, while maintaining competitive first class, business class, and economy class comfort levels. Moreover, this transport will render a minimal impact upon the environment, and will meet all Federal Aviation Administration Part 36, Stage III noise requirements. The cornerstone of The Edge's superior flight performance is its aerodynamically efficient, dual-configuration design incorporating variable-geometry wingtips. This arrangement combines the benefits of a high aspect ratio wing at takeoff and low cruising speeds with the high performance of an arrow-wing in supersonic cruise. And while the structural weight concerns relating to swinging wingtips are substantial, The Edge looks to ever-advancing material technologies to further increase its viability. Heeding well the lessons of the past, The Edge design holds economic feasibility as its primary focus. Therefore, in addition to its inherently superior aerodynamic performance, The Edge uses a lightweight, largely windowless configuration, relying on a synthetic vision system for outside viewing by both pilot and passengers. Additionally, a fly-by-light flight control system is incorporated to address aircraft supersonic cruise instability. The Edge will be produced at an estimated volume of 400 aircraft and will be offered to airlines in 2015 at $167 million per transport (1992 dollars).
Extended Klein edges in graphene.
He, Kuang; Robertson, Alex W; Lee, Sungwoo; Yoon, Euijoon; Lee, Gun-Do; Warner, Jamie H
2014-12-23
Graphene has three experimentally confirmed periodic edge terminations, zigzag, reconstructed 5-7, and arm-chair. Theory predicts a fourth periodic edge of graphene called the extended Klein (EK) edge, which consists of a series of single C atoms protruding from a zigzag edge. Here, we confirm the existence of EK edges in both graphene nanoribbons and on the edge of bulk graphene using atomic resolution imaging by aberration-corrected transmission electron microscopy. The formation of the EK edge stems from sputtering and reconstruction of the zigzag edge. Density functional theory reveals minimal energy for EK edge reconstruction and bond distortion both in and out of plane, supporting our TEM observations. The EK edge can now be included as the fourth member of observed periodic edge structures in graphene.
Research on Congestion Pricing in Multimode Traffic considering Delay and Emission
Hongna Dai
2015-01-01
Full Text Available Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.
Modeling Tiered Pricing in the Internet Transit Market
Valancius, Vytautas; Feamster, Nick; Johari, Ramesh; Vazirani, Vijay V
2011-01-01
ISPs are increasingly selling "tiered" contracts, which offer Internet connectivity to wholesale customers in bundles, at rates based on the cost of the links that the traffic in the bundle is traversing. Although providers have already begun to implement and deploy tiered pricing contracts, little is known about how such pricing affects ISPs and their customers. While contracts that sell connectivity on finer granularities improve market efficiency, they are also more costly for ISPs to implement and more difficult for customers to understand. In this work we present two contributions: (1) we develop a novel way of mapping traffic and topology data to a demand and cost model; and (2) we fit this model on three large real-world networks: an European transit ISP, a content distribution network, and an academic research network, and run counterfactuals to evaluate the effects of different pricing strategies on both the ISP profit and the consumer surplus. We highlight three core findings. First, ISPs gain most ...
A New Edge-directed Subpixel Edge Localization Method
于新瑞; 徐威; 王石刚; 李倩
2004-01-01
Localization of the inspected chip image is one of the key problems with machine vision aided surface mount devices (SMD) and other micro-electronic equipments. This paper presents a new edge-directed subpixel edge localization method. The image is divided into two regions, edge and non-edge, using edge detection to emphasize the edge feature. Since the edges of the chip image are straight, they have straight-line characteristics locally and globally. First,the line segments of the straight edge are located to subpixel precision, according to their local straight properties, in a 3 × 3 neighborhood of the edge region. Second, the subpixel midpoints of the line segments are computed. Finally, the straight edge is fitted using the midpoints and the least square method, according to its global straight property in the entire edge region. In this way, the edge is located to subpixel precision. While fitting the edge, the irregular points are eliminated by the angles of the line segments to improve the precision. We can also distinguish different edges and their intersections using the angles of the line segments and distances between the edge points, then give the vectorial result of the image edge with high precision.
Geloni, G.; Kocharyan, V.; Saldin, E.; Schneidmiller, E.; Yurkov, M.
2008-08-15
We formulate a complete theory of Edge Radiation based on a novel method relying on Fourier Optics techniques. Similar types of radiation like Transition UndulatorRadiation are addressed in the framework of the same formalism. Special attention is payed in discussing the validity of approximations upon which the theory is built. Our study makes consistent use of both similarity techniques and comparisons with numerical results from simulation. We discuss both near and far zone. Physical understanding of many asymptotes is discussed. Based on the solution of the field equation with a tensor Green's function technique, we also discuss an analytical model to describe the presence of a vacuum chamber. In particular, explicit calculations for a circular vacuum chamber are reported. Finally, we consider the use of Edge Radiation as a tool for electron beam diagnostics. We discuss Coherent Edge Radiation, Extraction of Edge Radiation by a mirror, and other issues becoming important at high electron energy and long radiation wavelength. Based on this work we also study the impact of Edge Radiation on XFEL setups and we discuss recent results. (orig.)
无
2006-01-01
Market-based reform of energy prices is the most effective approach to enhancing energy efficiency. The policies of energy conservation and enhancing energy efficiency in the 1 lth Five-year Plan period (2006-2010) work directly to set up a series of reform measures related to energy pricing by market mechanism. Energy price reform will deeply influence China's industrial interest pattern, and its development in the next five years and even 10 or 20 years.This paper analyzes the significance, timing, present status and problems related to energy price reform, and discusses the goal, principle and measures of coal, electricity, oil and gas price reform separately.
Industrial Pricing: Theory and Managerial Practice
Peter M. Noble; Gruca, Thomas S.
1999-01-01
We organize the existing theoretical pricing research into a new two-level framework for industrial goods pricing. The first level consists of four pricing situations: New Product, Competitive, Product Line, and Cost-based. The second level consists of the pricing strategies appropriate for a given situation. For example, within the new product pricing situation, there are three alternative pricing strategies: Skim, Penetration, and Experience Curve pricing. There are a total of ten pricing s...
Luciana Koprencka
2016-04-01
Full Text Available The real estate market is complex and influenced by too many factors. Real Estate market in Albania has experienced a boom after the 1990. We have inherited from the communist system a very poor market of housing. The number of dwellings in 1990 in Albania was 219 dwellings per 1000 inhabitants and the useful floor space was 5 m² per person, but in Bulgaria number of dwellings per 1,000 people varies 465 and in Romania average useful floor space per person was 37 sq. The data used in this study are derived from the database of the World Bank, the Institute of Statistics, reports of Bank of Albania also from information provided individually on the ground and different sources. In this study is analyzed the relationship that exists between economic growth, remittances and the price of dwellings in Albania. The dependent variable is the average price of housing in major cities of Albania. Independent variables in the model are GDP per capita and the remittances. The Econometric model is a Linear Regress equation and the period are the years from 1998 to 2013. The model used is the statistical program EViews 6.0. Unfortunately the information let the desired, so we do not have an official detailed information on prices of Albanian real estate market. In Albania few researchers have been studying real estate market in Albania.
Price setting in turbulent times
Ólafsson, Tjörvi; Pétursdóttir, Ásgerdur; Vignisdóttir, Karen Á.
. A second contribution to the literature is our analysis of the nexus between price setting and exchange rate movements, a topic that has attracted surprisingly limited attention in this survey-based literature. A novel aspect of our approach is to base our analysis on a categorisation of firms...... in the domestic market by their direct exposure to exchange rate movements captured by imported input costs as a share of total p duction costs. More exposed firms are found to be more likely to use state-dependent pricing, to adjust their prices in response to exchange rate changes, and to rely on increasing...... prices rather than decreasing costs to restore profit margins after an exchange rate depreciation. They also review their prices more often but nevertheless, surprisingly, have the same price change frequency as the median firm. On the other hand, price review frequency declines and time...
Prokop, Norman F (Inventor)
2016-01-01
Analog circuits for detecting edges in pixel arrays are disclosed. A comparator may be configured to receive an all pass signal and a low pass signal for a pixel intensity in an array of pixels. A latch may be configured to receive a counter signal and a latching signal from the comparator. The comparator may be configured to send the latching signal to the latch when the all pass signal is below the low pass signal minus an offset. The latch may be configured to hold a last negative edge location when the latching signal is received from the comparator.
Novel indexes based on network structure to indicate financial market
Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing
2016-02-01
There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.
Option Pricing when the Regime-Switching Risk is Priced
Tak Kuen Siu; Hailiang Yang
2009-01-01
We study the pricing of an option when the price dynamic of the underlying risky asset is governed by a Markov-modulated geometric Brownian motion. We suppose that the drift and volatility of the underlying risky asset are modulated by an observable continuous-time, finite-state Markov chain. We develop a twostage pricing model which can price both the diffusion risk and the regime-switching risk based on the Esscher transform and the minimization of the maximum entropy between an equivalent martingale measure and the real-world probability measure over different states. Numerical experiments are conducted and their results reveal that the impact of pricing regime-switching risk on the option prices is significant.
The price of anarchy in basketball
Skinner, Brian
2010-03-01
Optimizing the performance of a basketball offense may be viewed as a network problem, wherein each play represents a ``pathway'' through which the ball and players may move from origin (the in-bounds pass) to goal (the basket). Effective field goal percentages from the resulting shot attempts can be used to characterize the efficiency of each pathway. Inspired by recent discussions of the ``price of anarchy'' in traffic networks, this paper makes a formal analogy between a basketball offense and a simplified traffic network. The analysis suggests that there may be a significant difference between taking the highest-percentage shot each time down the court and playing the most efficient possible game. There may also be an analogue of Braess's Paradox in basketball, such that removing a key player from a team can result in the improvement of the team's offensive efficiency.
Market Confidence Predicts Stock Price: Beyond Supply and Demand
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing
2016-01-01
Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price. PMID:27391816
Market Confidence Predicts Stock Price: Beyond Supply and Demand.
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Zhang, Yuqing
2016-01-01
Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price.
Formation of an Integrated Stock Price Forecast Model in Lithuania
Audrius Dzikevičius
2016-12-01
Full Text Available Technical and fundamental analyses are widely used to forecast stock prices due to lack of knowledge of other modern models and methods such as Residual Income Model, ANN-APGARCH, Support Vector Machine, Probabilistic Neural Network and Genetic Fuzzy Systems. Although stock price forecast models integrating both technical and fundamental analyses are currently used widely, their integration is not justified comprehensively enough. This paper discusses theoretical one-factor and multi-factor stock price forecast models already applied by investors at a global level and determines possibility to create and apply practically a stock price forecast model which integrates fundamental and technical analysis with the reference to the Lithuanian stock market. The research is aimed to determine the relationship between stock prices of the 14 Lithuanian companies listed in the Main List by the Nasdaq OMX Baltic and various fundamental variables. Based on correlation and regression analysis results and application of c-Squared Test, ANOVA method, a general stock price forecast model is generated. This paper discusses practical implications how the developed model can be used to forecast stock prices by individual investors and suggests additional check measures.
Market Confidence Predicts Stock Price: Beyond Supply and Demand.
Xiao-Qian Sun
Full Text Available Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize market confidence, i.e., the ratio of the number of traders who is active in two successive trading days to the number of active traders in a certain trading day. Strong Granger causality is found between the index of market confidence and stock price. We further predict stock price by incorporating the index of market confidence into a neural network based on time series of stock price. Experimental results on 50 stocks in two Chinese Stock Exchanges demonstrate that the accuracy of stock price prediction is significantly improved by the inclusion of the market confidence index. This study sheds light on using cross-day trading behavior to characterize market confidence and to predict stock price.
Pricing Strategy versus Heterogeneous Shopping Behavior under Market Price Dispersion
Francisco Álvarez
2016-01-01
Full Text Available We consider the ubiquitous problem of a seller competing in a market of a product with dispersed prices and having limited information about both his competitors’ prices and the shopping behavior of his potential customers. Given the distribution of market prices, the distribution of consumers’ shopping behavior, and the seller’s cost as inputs, we find the computational solution for the pricing strategy that maximizes his expected profits. We analyze the seller’s solution with respect to different exogenous perturbations of parametric and functional inputs. For that purpose, we produce synthetic price data using the family of Generalized Error Distributions that includes normal and quasiuniform distributions as particular cases, and we also generate consumers’ shopping data from different behavioral assumptions. Our analysis shows that, beyond price mean and dispersion, the shape of the price distribution plays a significant role in the seller’s pricing solution. We focus on the seller’s response to an increasing diversity in consumers’ shopping behavior. We show that increasing heterogeneity in the shopping distribution typically lowers seller’s prices and expected profits.
Strategic pricing: hitting the mark with pricing strategies. Part 1.
Porn, L; Manning, M
1988-01-01
Efforts by government and business to reduce healthcare expenditures by fostering competition and reducing utilization have combined to redefine the basic economic structure of the healthcare delivery system. Increased competition among providers has prompted an increased awareness of strategic pricing as a means of achieving institutional goals and objectives. In this article, the first in a three-part series on strategic pricing, the authors examine some of the key theoretical considerations related to pricing strategies for healthcare providers. Future articles will examine practical applications as they relate to package pricing, discounting, per diem systems, and capitation arrangements.
Effects of coal prices on merchandise prices in China
Ding Zhihua; Zhou Meihua; Liu Yan
2011-01-01
Coal is the principal form of energy used in China.Hence,coal price variations are expected to have some influence on merchandise prices.Monthly data from January,2002,to October,2010,were used to construct a varying-parameter state space model,and an error correction model,to estimate the influence of coal prices on Chinese merchandise prices.The time lag and the dynamic relationship were determined from the data.A long term equilibrium relationship between coal price and the PPI,and the CPI,can be observed.The long term influence of coal price fluctuations on the PPI is 0.263％.The corresponding value for the CPI is 0.157％.The PPI shows an influence from coal price change in the first period of observation:by eight periods the influence is obvious,after which it diminishes.The effect of coal price change on the CPI is rather weak and has no long term memory.Analysis of variance shows a similar situation.The elasticity coefficient of coal prices on the CPI,or the PPI,fluctuates over the 2002-2004 period.From 2002 to 2007 the influence elasticity on the CPI declined and subsequently levelled off after 2009.
魏明桦; 郑金贵
2014-01-01
An improved BP neural network model is proposed to improve the precision of the prediction of agricultural products. Firstly, the factors of price fluctuation of agricultural products are gotten through the qualitative analysis and then use the MIV method to choose the strong influent factors as the input nodes of a neural network. Find the optimal structure of BP network through the improved learning algorithm, and then use the improved model to realize the agricultural high precision simulation of the product price.%为了提高农产品价格预测精度，提出一种改进的 BP 神经网络模型。先通过定性分析得到影响农产品价格波动的因子，然后采用MIV方法选择强影响力的因子作为神经网络输入节点。并采用改进的算法进行学习，寻找最优的BP网络结构。利用改进后的模型，实现了农产品价格的高精度仿真。
Pricing Decision Support System for Generation Companies in Electricity Market
FangDebin; WangXianjia
2005-01-01
In order to meet the requirement of separating power plants from power network and that of the competition based power transaction in power market, the pricing decision support system for generation companies (GCPDSS) is built in electricity market. This paper introduces the conception of intelligent decision support system (IDSS) and puts emphasis on the systematical structural framework,work process, design principal, and fundamental function of GCPDSS. The system has the module to analyze the cost, to forecast the demand of power, to construct the pricing strategies, to manage the pricing risk, and to dispatch giving the pricing strategies.The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decisions.
A model for managing edge effects in harvest scheduling using spatial optimization
Kai L. Ross; Sándor F. Tóth
2016-01-01
Actively managed forest stands can create new forest edges. If left unchecked over time and across space, forest operations such as clear-cuts can create complex networks of forest edges. Newly created edges alter the landscape and can affect many environmental factors. These altered environmental factors have a variety of impacts on forest growth and structure and can...
Kokholm, Thomas
The field of quantitative finance has been criticized in the mainstream media lately and been accused of being one of the causes of the financial crisis. Convenient as this explanation may be, my belief is that a part of the solution to the crisis is to use more (and not less) sophisticated....... With the existence of a liquid market for derivatives with variance as underlying, such as VIX options, VIX futures and a well-developed over-the-counter market for options on variance swaps, it is important to consider models that are able to fit these markets while consistently pricing vanilla options...
Sauer, Johannes
of biodiversity and the appropriate incorporation in stochastic fron-tier models to achieve more realistic measures of production efficiency. We use the empirical example of tobacco production drawing from as well as affecting species diversity in the surrounding forests. We apply a shadow profit distance....... Based on a biologically defined species diver-sity index we incorporate biodiversity either as a desirable output or biodiversity loss as a detrimental input. Beside quantitative shadow price measures the main contribu-tion of the work is the evidence that parametric scores of environmental efficiency...
Sauer, Johannes
. Based on a biologically defined species diver-sity index we incorporate biodiversity either as a desirable output or biodiversity loss as a detrimental input. Beside quantitative shadow price measures the main contribu-tion of the work is the evidence that parametric scores of environmental efficiency...... of biodiversity and the appropriate incorporation in stochastic fron-tier models to achieve more realistic measures of production efficiency. We use the empirical example of tobacco production drawing from as well as affecting species diversity in the surrounding forests. We apply a shadow profit distance...
van Damme, E.E.C.; Hurkens, S.
1998-01-01
We consider a linear price setting duopoly game with di®erentiated products and determine endogenously which of the players will lead and which will follow. While the follower role is most attractive for each firm, we show that waiting is more risky for the low cost firm so that, consequently, risk dominance considerations, as in Harsanyi and Selten (1988), allow the conclusion that only the high cost firm will choose to wait. Hence, the low cost firm will emerge as the end...
Hansen, Lars Gårn; Jensen, Frank
Weitzman (2002) studies the regulation of a fishery characterised by constant marginal harvest costs and shows that price regulation performs better than quantity regulation when the regulator is uncertain about the biological reproduction function (ecological uncertainty). Here, we initially...... uncertainty. We find that the gain from eliminating compliance uncertainty may be up to 5% of gross profit while the gain from eliminating ecological uncertainty is minimal. Under landing fee regulation, the entire gain from eliminating both types of uncertainty is captured, even if the regulator’s stock...
Behrmann, Gerd; Larsen, Kim Guldstrand; Rasmussen, Jacob Illum
2004-01-01
This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European proj...... projects VHS [22] and AMETIST [17] and are available in the recently released UPPAAL CORA [12], a variant of the real-time verification tool UPPAAL [20,5] specialized for cost-optimal reachability for the extended model of priced timed automata....
Superpixel edges for boundary detection
Moya, Mary M.; Koch, Mark W.
2016-07-12
Various embodiments presented herein relate to identifying one or more edges in a synthetic aperture radar (SAR) image comprising a plurality of superpixels. Superpixels sharing an edge (or boundary) can be identified and one or more properties of the shared superpixels can be compared to determine whether the superpixels form the same or two different features. Where the superpixels form the same feature the edge is identified as an internal edge. Where the superpixels form two different features, the edge is identified as an external edge. Based upon classification of the superpixels, the external edge can be further determined to form part of a roof, wall, etc. The superpixels can be formed from a speckle-reduced SAR image product formed from a registered stack of SAR images, which is further segmented into a plurality of superpixels. The edge identification process is applied to the SAR image comprising the superpixels and edges.
A Multiperiod Equilibrium Pricing Model
Minsuk Kwak
2014-01-01
Full Text Available We propose an equilibrium pricing model in a dynamic multiperiod stochastic framework with uncertain income. There are one tradable risky asset (stock/commodity, one nontradable underlying (temperature, and also a contingent claim (weather derivative written on the tradable risky asset and the nontradable underlying in the market. The price of the contingent claim is priced in equilibrium by optimal strategies of representative agent and market clearing condition. The risk preferences are of exponential type with a stochastic coefficient of risk aversion. Both subgame perfect strategy and naive strategy are considered and the corresponding equilibrium prices are derived. From the numerical result we examine how the equilibrium prices vary in response to changes in model parameters and highlight the importance of our equilibrium pricing principle.
2016-11-15
This major final rule addresses changes to the physician fee schedule and other Medicare Part B payment policies, such as changes to the Value Modifier, to ensure that our payment systems are updated to reflect changes in medical practice and the relative value of services, as well as changes in the statute. This final rule also includes changes related to the Medicare Shared Savings Program, requirements for Medicare Advantage Provider Networks, and provides for the release of certain pricing data from Medicare Advantage bids and of data from medical loss ratio reports submitted by Medicare health and drug plans. In addition, this final rule expands the Medicare Diabetes Prevention Program model.
Price and consumption of tobacco
Virendra Singh; Bharat Bhushan Sharma; Puneet Saxena; Hardayal Meena; Daya Krishan Mangal
2012-01-01
Background: It is thought that price increase in tobacco products leads to reduced consumption. Though many studies have substantiated this concept, it has not been well studied in India. Recently, price of tobacco products was increased due to ban on plastic sachets of chewing tobacco and increased tax in Rajasthan. This study was designed to evaluate the effect of price rise on overall consumption of tobacco in Jaipur city, Rajasthan. Materials and Methods: This study was carried out in Jai...
Cost minimization and asset pricing
Robert G. Chambers; John Quiggin
2005-01-01
A cost-based approach to asset-pricing equilibrium relationships is developed. A cost function induces a stochastic discount factor (pricing kernel) that is a function of random output, prices, and capital stockt. By eliminating opportunities for arbitrage between financial markets and the production technology, firms minimize the current cost of future consumption. The first-order conditions for this cost minimization problem generate the stochastic discount factor. The cost-based approach i...
Essays in Empirical Asset Pricing
Rzeznik, Aleksandra
This thesis consists of three essays investigating financial and real estate markets and identifying a relationship between them. A 2008 financial crises provides a perfect example of sizeable interactions between US housing market and equity prices, where a negative shock to house prices trigger...... a word-wide recession. Therefore, understanding forces driving investors behaviour and preferences, which in turn affect asset prices in both equity and housing market are of great interest....
RESTAURANT NO. 3 : PRICE INCREASES
Restaurant Supervisory Committee
2002-01-01
'AVENANCE', the concession holder of Restaurant no. 3 (bldg. 866 - Prévessin site), has submitted to the Restaurant Supervisory Committee a request to increase its prices. After close examination, the Committee has established that the proposed increases are compatible with the relevant price indexing mechanisms and other contractual conditions. The new prices will apply as from Monday, June 3, 2002. Restaurant Supervisory Committee, tel. 77551
Testing Monotonicity of Pricing Kernels
Timofeev, Roman
2007-01-01
In this master thesis a mechanism to test mononicity of empirical pricing kernels (EPK) is presented. By testing monotonicity of pricing kernel we can determine whether utility function is concave or not. Strictly decreasing pricing kernel corresponds to concave utility function while non-decreasing EPK means that utility function contains some non-concave regions. Risk averse behavior is usually described by concave utility function and considered to be a cornerstone of classical behavioral ...
Essays in Empirical Asset Pricing
Rzeznik, Aleksandra
This thesis consists of three essays investigating financial and real estate markets and identifying a relationship between them. A 2008 financial crises provides a perfect example of sizeable interactions between US housing market and equity prices, where a negative shock to house prices triggered...... a word-wide recession. Therefore, understanding forces driving investors behaviour and preferences, which in turn affect asset prices in both equity and housing market are of great interest....
Corn prices and alcohol production
Wangsness, W.
1979-09-01
Corn has attracted the most attention as a feedstock for alcohol production. The economics are computed on the basis of fixed costs for labor, taxes, depreciation, heat, and enzymes. Changes in feedstock prices are shown to determine whether corn is used for energy or protein as cattle feed. Comparisons of gasoline refined from imported oil and gasohol are made for a range of prices per bushel and oil prices per barrel. (DCK)
Baena, D. Eduardo Martin [Endesa, Principe de Vergara 187, Madrid (Spain)
1998-07-01
It looks like that all over the World things are changing. Many countries, Spain among them, where electricity regulations were usual, are changing their regulatory mainframe. Since January 1, 1998, electricity production is a deregulated activity in Spain. There has to be open market competition. Prices that are very important for the time coming, have to cover the production cost plus some profits in order to maintain the company profitability. This cultural change applies to all our production facilities, including nuclear power plants. Taking into account this new situation and the nuclear competitiveness, it is important for all of us to understand this issue. As it is well known, nuclear energy is capital intensive, that means it has to compete as base load units due to their low operating costs and their large capital ones. For that reason it is important to reduce as much as possible the operating and maintenance cost as well as the fuel one, which will allow nuclear plants to compete in marginal costs with others units. Nuclear energy, in Spain, is not going to fix the pool price but it has to recover some depreciation through it, the remaining being recovered by the recognition of an important part of the stranded cost. (author)
Pricing hazardous substance emissions
Staring, Knut; Vennemo, Haakon
1997-12-31
This report discusses pricing of emissions to air of several harmful substances. It combines ranking indices for environmentally harmful substances with economic valuation data to yield price estimates. The ranking methods are discussed and a relative index established. Given the relative ranking of the substances, they all become valued by assigning a value to one of them, the `anchor` substance, for which lead is selected. Valuations are provided for 19 hazardous substances that are often subject to environmental regulations. They include dioxins, TBT, etc. The study concludes with a discussion of other categories of substances as well as uncertainties and possible refinements. When the valuations are related to CO, NOx, SOx and PM 10, the index system undervalues these pollutants as compared to other studies. The scope is limited to the outdoor environment and does not include global warming and eutrophication. The indices are based on toxicity and so do not apply to CO{sub 2} or other substances that are biologically harmless. The index values are not necessarily valid for all countries and should be considered as preliminary. 18 refs., 6 tabs.
TOURISM MARKET: PRICING ISSUES
Irina A. Kiseleva
2016-01-01
Full Text Available The article is devoted to the actual topic of our time - the development of tourism services. The development of tourism is the leading technology trend dynamics maroon economic caused social restructuring of modern society. Macroeconomic Financial Statistics conrms the minimum amplitude of cyclical uctuations in the service sector, which turns it into countercyclical tool. In the Russian Federation the economic problem of a state policy in the sphere of tourist services is defined - to having turned tourism in competitive, innovative, countercyclical, and highly protable sector of national business. In article pricing factors are dened and are dened key of them, responsible for the cost of a tourist product. This work answers such questions of travel company as: denition of optimum group, formation of a transport tariff, structure of a tourist product on the main and accompanying services and their range, ways of sale. A practical advice by calculation of expenses is given. Correlation and regression and cluster analyses acted as research tools when performing work. In article the conclusion is drawn that the main methods of marketing management of pricing in the market of tourist services are: transition to the unified technology of granting a service on the basis of ISO; intensication and integration of the sphere of production and services
Reciprocity, World Prices and Welfare
Raimondos-Møller, Pascalis; Woodland, Alan D.
We examine in detail the circumstances under which reciprocity, as defined in Bagwell and Staiger (1999), leads to fixed world prices. We show that a change of tariffs satisfying reciprocity does not necessarily imply constant world prices in a world of many goods and countries. While...... it is possible to find tariff reforms that are consistent with both reciprocity and constant world prices, these reforms do not follow from the reciprocity condition, but rather from the requirement of unchanged world prices. We propose an alternative reciprocity rule that is guaranteed to raise the welfare...
Transmission pricing: paradigms and methodologies
Shirmohammadi, Dariush [Pacific Gas and Electric Co., San Francisco, CA (United States); Vieira Filho, Xisto; Gorenstin, Boris [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil); Pereira, Mario V.P. [Power System Research, Rio de Janeiro, RJ (Brazil)
1994-12-31
In this paper we describe the principles of several paradigms and methodologies for pricing transmission services. The paper outlines some of the main characteristics of these paradigms and methodologies such as where they may be used for best results. Due to their popularity, power flow based MW-mile and short run marginal cost pricing methodologies will be covered in some detail. We conclude the paper with examples of the application of these two pricing methodologies for pricing transmission services in Brazil. (author) 25 refs., 2 tabs.
Price setting in turbulent times
Ólafsson, Tjörvi; Pétursdóttir, Ásgerdur; Vignisdóttir, Karen Á.
-dependent pricing increases as domestic labour costs rise relative to total production costs. The results provide important insight into inflation dynamics due to an interaction between high and asymmetric exchange rate pass-through and price indexation. This interaction causes an exchange rate depreciation...... in the domestic market by their direct exposure to exchange rate movements captured by imported input costs as a share of total p duction costs. More exposed firms are found to be more likely to use state-dependent pricing, to adjust their prices in response to exchange rate changes, and to rely on increasing...
Price transparency for medical devices.
Pauly, Mark V; Burns, Lawton R
2008-01-01
Hospital buyers of medical devices contract with manufacturers with market power that sell differentiated products. The medical staff strongly influences hospitals' choice of devices. Sellers have sought to limit disclosure of transaction prices. Policy-makers have proposed legislation mandating disclosure, in the interest of greater transparency. We discuss why a manufacturer might charge different prices to different hospitals, the role that secrecy plays, and the consequences of secrecy versus disclosure. We argue that hospital-physician relationships are key to understanding what manufacturers gain from price discrimination. Price disclosure can catalyze a restructuring of those relationships, which, in turn, can improve hospital bargaining.
Artificial Shortages and Strategic Pricing
Partha Gangopadhyay
2012-01-01
Full Text Available Problem statement: We consider a monopolist who manipulates the market by artificially creating shortages that result in an increase in current price that, in turn, boosts demand for the product in subsequent periods. The approach is to develop an intertemporal model of pricing strategy for a monopolist. Approach: The postulated pricing strategy creates an incentive for producers to reduce current supply and raise current prices and sacrifice current profits in order to increase future profits. The main problem is to explain the precise mathematical conditions under which the pricing strategy will be chosen by a monopolist. Results: We derive the optimal pricing strategy to argue that the monopolist has an incentive to adopt simple market manipulation that calls forth a close examination of issues concerning deregulation. Conclusion: The paper examines two possible strategies for a typical monopolist-strategic pricing vis-a-vis a myopic pricing. The intuition is that the monopolist can manipulate the market by artificially creating shortages that result in an increase in current price that, in turn, boosts demand for the product in subsequent periods.
无
2005-01-01
Prices of light rare earth products in Baotou rose on the full scale in July. Price of lanthana reached RMB 12,000 - 13,000/t, that of ceria RMB 12,000/t, praseodymia RMB 70,000 - 72,000/t, Pr-Nd oxides RMB 52,000/t, neodymia RMB 65,000/t. Despite the high price of Pr-Nd oxides and neodymia, no goods are available at hand. Price rising is attributed to enforcement of environmental protection policy and heightening project suspending of Baogang tailings dam. RE separation enterprises along Yellow River have ...
Price Strategies in Banking Marketing
Iuliana Cetina
2007-01-01
Full Text Available All organizations must settle a price for the services they offer. The price for services is an important element of the marketing mix, being an important income source for the organization. The settlement of a correct price, both for the market and the competition, is a significant element for the sector of financial - banking services. Another important factor to take into consideration is the fact that the banks do not settle only the prices for individual services, but also coordinate their prices for service packages. As the competition in the financial - banking services has intensified, the settlement of correct prices has become an essential element for the marketing strategy. Nevertheless it is important to remind that the price is not a central element. There are other significant grounds, the price being only one of the elements of the marketing mix. Although in Romania many customers may be sensitive in present to the price, as the competition will increase, the quality of the services will become more important to the customers, and the demand will be complex.
Edge detection by nonlinear dynamics
Wong, Yiu-fai
1994-07-01
We demonstrate how the formulation of a nonlinear scale-space filter can be used for edge detection and junction analysis. By casting edge-preserving filtering in terms of maximizing information content subject to an average cost function, the computed cost at each pixel location becomes a local measure of edgeness. This computation depends on a single scale parameter and the given image data. Unlike previous approaches which require careful tuning of the filter kernels for various types of edges, our scheme is general enough to be able to handle different edges, such as lines, step-edges, corners and junctions. Anisotropy in the data is handled automatically by the nonlinear dynamics.
Graphene edges; localized edge state and electron wave interference
Enoki Toshiaki
2012-03-01
Full Text Available The electronic structure of massless Dirac fermion in the graphene hexagonal bipartite is seriously modified by the presence of edges depending on the edge chirality. In the zigzag edge, strongly spin polarized nonbonding edge state is created as a consequence of broken symmetry of pseudo-spin. In the scattering at armchair edges, the K-K’ intervalley transition gives rise to electron wave interference. The presence of edge state in zigzag edges is observed in ultra-high vacuum STM/STS observations. The electron wave interference phenomenon in the armchair edge is observed in the Raman G-band and the honeycomb superlattice pattern with its fine structure in STM images.
李永亮; 张怀清; 林辉
2012-01-01
利用便携式ASD野外光谱辐射仪对杉木冠层叶片光谱进行测定,同时以分光光度法对叶片叶绿素含量进行提取.样本经均值处理、平滑处理和微分处理后,进行红边参数提取.对11个红边参数以PCA方法进行降维,将得到的前7个主成分得分作为网络输入参数,叶绿素含量作为网络输出参数,以遗传算法(GA)优化网络初始权值阈值,建立隐含层神经元数分别为4,6,8,10,12和14的6种单隐层BP神经网络模型.以R2,RMSE和相对误差作为模型精度检验标准,结果表明:6种模型预测精度均可达到92.0％以上,其中隐含层神经元数为10时,预测精度最高,可达97.372％.说明此种模型可对杉木冠层叶片叶绿素含量进行高精度估算.%High-precision estimation model of arbor canopy chlorophyll content is important to forestry and ecology. The spectral reflectance of canopy was measured by ASD FieldSpec and the chlorophyll content was measured by spectrophotometry at the same time. The sample data were pretreated by the methods of mean, smoothing and derivative, and then the red edge parameters of samples were extracted from the pretreated spectra data. The eleven red edge parameters were analyzed with principal component analysis ( PCA). The anterior 7 principal components computed by PCA were used as the input variables of back-propagation artificial neural network (BP-ANN) which included one hidden layer which had four, six, eight, ten, twelve or fourteen neurons, while the chlorophyll content was used as the output variables of BP-ANN, and then the three layers BP-ANN discrimination model was built. Weight value and threshold value of this model were optimized by using genetic algorithm. The fitness between the predicted value and the measured value was tested by the determination coefficient, the lowest root mean-square error and the average relative error. The results show that the precisions of six models are all above 92. 0% and the
Modeling the Effect of Oil Price on Global Fertilizer Prices
P-Y. Chen (Ping-Yu); C-L. Chang (Chia-Lin); C-C. Chen (Chi-Chung); M.J. McAleer (Michael)
2010-01-01
textabstractThe main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the
Consumer food choices: the role of price and pricing strategies.
Steenhuis, Ingrid H M; Waterlander, Wilma E; de Mul, Anika
2011-12-01
To study differences in the role of price and value in food choice between low-income and higher-income consumers and to study the perception of consumers about pricing strategies that are of relevance during grocery shopping. A cross-sectional study was conducted using structured, written questionnaires. Food choice motives as well as price perceptions and opinion on pricing strategies were measured. The study was carried out in point-of-purchase settings, i.e. supermarkets, fast-food restaurants and sports canteens. Adults (n 159) visiting a point-of-purchase setting were included. Price is an important factor in food choice, especially for low-income consumers. Low-income consumers were significantly more conscious of value and price than higher-income consumers. The most attractive strategies, according to the consumers, were discounting healthy food more often and applying a lower VAT (Value Added Tax) rate on healthy food. Low-income consumers differ in their preferences for pricing strategies. Since price is more important for low-income consumers we recommend mainly focusing on their preferences and needs.
48 CFR 852.236-82 - Payments under fixed-price construction contracts (without NAS).
2010-10-01
... construction contracts (without NAS). 852.236-82 Section 852.236-82 Federal Acquisition Regulations System... Provisions and Clauses 852.236-82 Payments under fixed-price construction contracts (without NAS). As... “Network Analysis System (NAS).” Payments Under Fixed-Price Construction Contracts (APR 1984) The...
Pricing Strategies and Models for the Provision of Digitized Texts in Higher Education.
Hardy, Rachel; Oppenheim, Charles; Rubbert, Iris
2002-01-01
Describes research into charging mechanisms for the delivery of digitized texts to higher education students in the United Kingdom and discusses the need for a satisfactory pricing model. Explains the HERON (Higher Education Resources On-Demand) and PELICAN (Pricing Experiment Library Information Cooperative Network) projects and considers…
Nedospasov, A. V.
1992-12-01
Edge turbulence is of decisive importance for the distribution of particle and energy fluxes to the walls of tokamaks. Despite the availability of extensive experimental data on the turbulence properties, its nature still remains a subject for discussion. This paper contains a review of the most recent theoretical and experimental studies in the field, including mainly the studies to which Wootton (A.J. Wooton, J. Nucl. Mater. 176 & 177 (1990) 77) referred to most in his review at PSI-9 and those published later. The available theoretical models of edge turbulence with volume dissipation due to collisions fail to fully interpret the entire combination of experimental facts. In the scrape-off layer of a tokamak the dissipation prevails due to the flow of current through potential shifts near the surface of limiters of divertor plates. The different origins of turbulence at the edge and in the core plasma due to such dissipation are discussed in this paper. Recent data on the electron temperature fluctuations enabled one to evaluate the electric probe measurements of turbulent flows of particles and heat critically. The latest data on the suppression of turbulence in the case of L-H transitions are given. In doing so, the possibility of exciting current instabilities in biasing experiments (rather than only to the suppression of existing turbulence) is given some attention. Possible objectives of further studies are also discussed.
Colombian exports rise as prices rocket
Howland, J.
2001-04-01
The Colombian coal industry is in the throes of a boom period, fuelled primarily by a huge US appetite that is sucking in virtually all the available spot coal at prices now edging over 40 dollars for a standard product. With the US moving towards its summer, a period of high power demand, US domestic supplies are still tight and power station stocks have not been replenished from the winter, indicating that this US hunger will be maintained. With so much demand, a McCloskey's Coal Report survey predicts that export levels could increase by 4.5 mt this year on 2000 levels of 34.3. mt. This looks like it could be easily realised, with all the country's export producers eager to take advantage of the high prices. The article discusses the state of business of Carbocol, the former state owned coal mining company, Drummond, the owner and operator of Colombia's second largest coal mining operation, the La Loma mine, and of other minor producers. It gives a table of destinations of Colombian coal exports in the year 2000. 2 refs., 1 tab., 1 photo.
Obesity and Supermarket Access: Proximity or Price?
Aggarwal, Anju; Hurvitz, Philip M.; Monsivais, Pablo; Moudon, Anne V
2012-01-01
Objectives. We examined whether physical proximity to supermarkets or supermarket price was more strongly associated with obesity risk. Methods. The Seattle Obesity Study (SOS) collected and geocoded data on home addresses and food shopping destinations for a representative sample of adult residents of King County, Washington. Supermarkets were stratified into 3 price levels based on average cost of the market basket. Sociodemographic and health data were obtained from a telephone survey. Modified Poisson regression was used to test the associations between obesity and supermarket variables. Results. Only 1 in 7 respondents reported shopping at the nearest supermarket. The risk of obesity was not associated with street network distances between home and the nearest supermarket or the supermarket that SOS participants reported as their primary food source. The type of supermarket, by price, was found to be inversely and significantly associated with obesity rates, even after adjusting for individual-level sociodemographic and lifestyle variables, and proximity measures (adjusted relative risk = 0.34; 95% confidence interval = 0.19, 0.63) Conclusions. Improving physical access to supermarkets may be one strategy to deal with the obesity epidemic; improving economic access to healthy foods is another. PMID:22698052
Pricing effects on food choices.
French, Simone A
2003-03-01
Individual dietary choices are primarily influenced by such considerations as taste, cost, convenience and nutritional value of foods. The current obesity epidemic has been linked to excessive consumption of added sugars and fat, as well as to sedentary lifestyles. Fat and sugar provide dietary energy at very low cost. Food pricing and marketing practices are therefore an essential component of the eating environment. Recent studies have applied economic theories to changing dietary behavior. Price reduction strategies promote the choice of targeted foods by lowering their cost relative to alternative food choices. Two community-based intervention studies used price reductions to promote the increased purchase of targeted foods. The first study examined lower prices and point-of-purchase promotion on sales of lower fat vending machine snacks in 12 work sites and 12 secondary schools. Price reductions of 10%, 25% and 50% on lower fat snacks resulted in an increase in sales of 9%, 39% and 93%, respectively, compared with usual price conditions. The second study examined the impact of a 50% price reduction on fresh fruit and baby carrots in two secondary school cafeterias. Compared with usual price conditions, price reductions resulted in a four-fold increase in fresh fruit sales and a two-fold increase in baby carrot sales. Both studies demonstrate that price reductions are an effective strategy to increase the purchase of more healthful foods in community-based settings such as work sites and schools. Results were generalizable across various food types and populations. Reducing prices on healthful foods is a public health strategy that should be implemented through policy initiatives and industry collaborations.
Considerations regarding price in oligopolistic structured markets
Ciobanu, R.
2011-01-01
Full Text Available Economists report price rigidity in markets with oligopolistic structures, while explaining the phenomenon. If an oligopolistic firm raises prices, other prices will remain stable in oligopolistic firms, so we will see a significant decrease in sales volume in the firm which increased prices. To avoid this situation an oligopolistic company will not initiate price increases. If oligopolistic firms lower prices, other oligopolistic firms will reduce prices promptly and the result will be that of lower volume of sales - will sell the same physical volume of goods but at a lower price. To avoid this situation, the company will not initiate oligopolistic price decreases.
Factory Gate Pricing : An Analysis of the Dutch Retail Distribution
Le Blanc, H.M.; Cruijssen, F.C.A.M.; Fleuren, H.A.; de Koster, M.B.M.
2004-01-01
Factory Gate Pricing (FGP) is a relatively new phenomenon in retail distribution.Under FGP, products are no longer delivered at the retailer distribution center, but collected by the retailer at the factory gates of the suppliers.Owing to both the asymmetry in the distribution networks (the supplier
Factory Gate Pricing: An Analysis of the Dutch Retail Distribution
H.M. le Blanc; F. Cruijssen (Frans); H.A. Fleuren; M.B.M. de Koster (René)
2004-01-01
textabstractFactory Gate Pricing (FGP) is a relatively new phenomenon in retail distribution. Under FGP, products are no longer delivered at the retailer distribution center, but collected by the retailer at the factory gates of the suppliers. Owing to both the asymmetry in the distribution networks
UPPAAL-SMC: Statistical Model Checking for Priced Timed Automata
Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand
2012-01-01
This paper offers a survey of U PPAAL - SMC, a major extension of the real-time verification tool U PPAAL. U PPAAL - SMC allows for the efficient analysis of performance properties of networks of priced timed automata under a natural stochastic semantics. In particular, U PPAAL - SMC relies on a ...
Smoothness in Binomial Edge Ideals
Hamid Damadi
2016-06-01
Full Text Available In this paper we study some geometric properties of the algebraic set associated to the binomial edge ideal of a graph. We study the singularity and smoothness of the algebraic set associated to the binomial edge ideal of a graph. Some of these algebraic sets are irreducible and some of them are reducible. If every irreducible component of the algebraic set is smooth we call the graph an edge smooth graph, otherwise it is called an edge singular graph. We show that complete graphs are edge smooth and introduce two conditions such that the graph G is edge singular if and only if it satisfies these conditions. Then, it is shown that cycles and most of trees are edge singular. In addition, it is proved that complete bipartite graphs are edge smooth.
New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity
Brown, Molly E.; Tondel, Fabien; Thorne, Jennifer A.; Essam, Timothy; Mann, Bristol F.; Stabler, Blake; Eilerts, Gary
2011-01-01
Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.