Evaluation model based on support vector machine for green coal supplier in electric power supply chain

2011 ◽  
Author(s):  
Qiang Wang ◽  
Kin Keung Lai ◽  
Dongxiao Niu
Keyword(s):  
Support Vector Machine ◽  
Supply Chain ◽  
Electric Power ◽  
Power Supply ◽  
Evaluation Model ◽  
Support Vector ◽  
Electric Power Supply ◽  
Model Based

scholarly journals Electric power supply chain networks design featuring differential pricing and preventive maintenance

2021 ◽  
Author(s):  
Yu-Chung Tsao ◽  
Thuy-Linh Vu ◽  
Jye-Chyi Lu
Keyword(s):  
Supply Chain ◽  
Electric Power ◽  
Power Supply ◽  
Preventive Maintenance ◽  
Power Plants ◽  
Network Design Problem ◽  
Supply Chain Network ◽  
Electric Power Supply ◽  
Power Company ◽  
Differential Pricing

The electric power supply chain network plays an important role in the world economy. It powers our homes, offices, and industries and runs various forms of transportation. This paper considers an electric power supply chain network design problem featuring differential pricing and preventive maintenance. We demonstrate that this general model can be formulated as the centralized and decentralized supply chain models. A continuous approximation approach is used to model the problems. The objective of these models is to determine the optimal power plants’ service area, electricity price, and preventive maintenance budget while maximizing the total network profit or the own organization’s benefits. Our model is applied to the case of a power company in northern Vietnam. We show that the proposed approach can be used to address real-world cases effectively. The results demonstrate that the use of differential pricing policy and preventive maintenance could much enhance power company profit.

Sound feature space effects on the performance of annoyance evaluation model based on support vector machine

2019 ◽  
Vol 154 ◽  
pp. 99-113 ◽  
Author(s):  
Tianpei Feng ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Ping Zhou ◽  
Hui Guo ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Evaluation Model ◽  
Feature Space ◽  
Support Vector ◽  
Model Based ◽  
Space Effects

Quantitative analysis of enterprise chain risk based on SVM algorithm and mathematical fuzzy set

2020 ◽  
Vol 39 (4) ◽  
pp. 5773-5783
Author(s):  
Gebing Sun
Keyword(s):  
Support Vector Machine ◽  
Supply Chain ◽  
Simulated Annealing ◽  
Quantitative Analysis ◽  
Fuzzy Set ◽  
Evaluation Model ◽  
Market Competition ◽  
Normal Operation ◽  
Support Vector ◽  
Svm Algorithm

Under the guidance and practice of lean production, just in time production and other advanced theories, the relationship between enterprises is becoming more and more closely. In order to cope with more fierce market competition, manufacturing enterprises began to strengthen cooperation with partners in the supply chain, gather resources, improve competitiveness and jointly fight against competitors. In these decades, the competition among enterprises is gradually replaced by the competition among supply chains. In this paper, the author makes quantitative analysis of enterprise chain risk based on SVM algorithm and mathematical fuzzy set. Support vector machine (SVM) is a machine learning method, has strong generalization ability and accuracy. By analyzing dexterity affects the normal operation of the supply chain risk factors, we use simulated annealing –mathematical fuzzy of the risk evaluation, it indicates that the model in risk assessment is applicable through empirical research. According to the data obtained, the simulated annealing –support vector machine evaluation model were trained and tested; the explanation on the choice of kernel function of the process of construction of the evaluation model, the parameters of the model to determine some key problems.

Flood Disaster Evaluation Model Based on Kernel Dual Optimization Support Vector Machine

2013 ◽  
Vol 12 (12) ◽  
pp. 2412-2418 ◽  
Author(s):  
Weiping Deng ◽  
Jianzhong Zhou ◽  
Qiang Zou ◽  
Jian Xiao ◽  
Yongchuan Zhang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Evaluation Model ◽  
Flood Disaster ◽  
Support Vector ◽  
Model Based

scholarly journals Modeling of Electric Power Supply Chain Networks with Fuel Suppliers via Variational Inequalities

2007 ◽  
Vol 8 (1) ◽  
Author(s):  
Dmytro Matsypura ◽  
Anna Nagurney ◽  
Zugang Liu
Keyword(s):  
Supply Chain ◽  
Electric Power ◽  
Flow Pattern ◽  
Power Supply ◽  
Service Providers ◽  
Electric Power Industry ◽  
The United States ◽  
Qualitative Properties ◽  
Existence Of A Solution ◽  
Electric Power Supply

The electric power industry in the United States and in other countries is undergoing profound regulatory and operational changes. The underlying rationale behind these transformations is to move once highly monopolized vertically-integrated industry from a centralized operation approach to a competitive one. The emerging competitive markets and an increase in the number of market participants have, in turn, fundamentally changed not only electricity trading patterns but also the structure of the electric power supply chains. This new framework requires new mathematical and engineering models and associated algorithmic tools. Moreover, the availability of fuels for electric power generation is a topic of both economic importance and national security. This paper uses the model developed by Nagurney and Matsypura (2004, 2006) as the foundation for the introduction of explicit fuel suppliers, in the case of nonrenewable and/or renewable fuels, and their optimizing behavior, into a general electric power supply chain network model along with "direct-supply" generation. We derive the optimality conditions for the various decision-makers, including fuel suppliers, power generators, suppliers, as well as the transmission service providers and the consumers at the demand markets. We establish that the governing equilibrium conditions satisfy a finite-dimensional variational inequality problem. We provide qualitative properties of the equilibrium flow pattern; in particular, existence of a solution and uniqueness under suitable assumptions. Finally, we discuss how the equilibrium fuel supply and electric power flow pattern can be computed.

Sign in / Sign up

Export Citation Format

Share Document