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Entropy generation minimization: A practical approach for performance evaluation of temperature cascaded co-generation plants

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ENERGY 2012年第1期46卷 493-521页

作者： Myat, Aung Thu, Kyaw Kim, Young Deuk Saha, Bidyut Baran Ng, Kim Choon ASTAR Inst Chem & Engn Sci Expt Power Grid Ctr Jurong Isl 627590 Singapore Natl Univ Singapore Dept Mech Engn Singapore 117576 Singapore King Abdullah Univ Sci & Technol Water Desalinat & Reuse Ctr Thuwal 239556900 Saudi Arabia Kyushu Univ Dept Mech Engn Nishi Ku Fukuoka 8190395 Japan Kyushu Univ Int Inst Carbon Neutral Energy Res WPI I2CNER Fukuoka 8190395 Japan

We present a practical tool that employs entropy generation minimization (EGM) approach for an in-depth performance evaluation of a co-generation plant with a temperature-cascaded concept. Co-generation plant produces useful effect production sequentially, i.e., (i) electricity from the micro-turbines, (ii) low pressure steam at 250 degrees C or about 8-10 bars, (iii) cooling capacity of 4 refrigeration tones (Rtons) and (iv) dehumidification of outdoor air for air conditioned space. The main objective is to configure the most efficient configuration of producing power and heat. We employed entropy generation minimization (EGM) which reflects to minimize the dissipative losses and maximize the cycle efficiency of the individual thermally activated systems. The minimization of dissipative losses or EGM is performed in two steps namely, (i) adjusting heat source temperatures for the heat-fired cycles and (ii) the use of Genetic algorithm (GA), to seek out the sensitivity of heat transfer areas, flow rates of working fluids, inlet temperatures of heat sources and coolant, etc., over the anticipated range of operation to achieve maximum efficiency. With EGM equipped with GA, we verified that the local minimization of entropy generation individually at each of the heat-activated processes would lead to the maximum efficiency of the system. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.

关键词： Temperature cascaded co-generation Adsorption Absorption Specific entropy generation Optimization generic algorithm

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Flexible Transmission Planning Considering Growing Uncertainties from Renewable Energy Integration

Flexible Transmission Planning Considering Growing Uncertain...

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IEEE International Conference on Power System Technology (POWERCON)

作者： Ren, Hui Fan, Xiaozhou Watts, David Lv, Xingchen North China Elect Power Univ Dept Elect Engn Baoding 071003 Hebei Peoples R China Pontificia Univ Catolica Chile Santiago Chile

ISBN: (纸本)9781467328685

Power systems are set to undergo dramatic changes driven by several factors ranging from climate change to technological developments. It is expected that networks will become more flexible to deal with increasing uncertainties, in those coming from future generation technologies and their locations as well as those from system operation practices. These developments will require fundamental changes in the way power systems are planned. This paper introduces a method of flexible transmission network planning with the traditional corrective control action assumed in the course of network planning. A two-stage solution algorithm is proposed combing Genetic algorithm and Monte Carlo simulation. Candidate planning schemes are decided by Genetic algorithm. Monte Carlo simulation and sensitivity method are used to find the most vulnerable part of the network, and then decides the amended control devices needed to be installed to achieve the optimum objective function and satisfy operational constraints (for each tested planning scheme). Discrete constraints associated with voltage control devices are included to make the simulation more realistic. The most flexible planning scheme is then defined as the one which needs the least investment on extra control devices. The proposed approach is implemented on an 18-bus test system and its feasibility is demonstrated.

关键词： Flexible transmission planning generic algorithm Monte Carlo simulation Sensitivity

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Improvement Intrusion Detection Based on SVM

Improvement Intrusion Detection Based on SVM

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3rd International Conference on Information Computing and Applications (ICICA 2012)

作者： Zhao, Jian-hua Li, Wei-hua Northwestern Polytech Univ Coll Comp Xian 710072 Peoples R China ShangLuo Univ Dept Comp Sci Shangluo Peoples R China

ISBN: (纸本)9783642340406

In order to improve the classification effectiveness of SVM (Support Vector Machine), new model is provided to optimize and. improve it. Penalty parameter c and kernel function parameter g of SVM are optimized using genetic algorithm of binary coding, and the optimized model GA-SVM is established. The dimensionality of input sample for SVM is reduced by PCA (Principal Component Analysis) and the model GA-PCA-SVM is established. The famous KDD Cup 1999 dataset is used to evaluate the proposed model and experiment is carried out based on GA-SVM and GA-PCA-SVM. By comparison, the results show that the genetic algorithm optimization improves the classification accuracy rate of SVM and PCA operation shorts the training time and test time.

关键词： Support Vector Machine generic algorithm Classification Intrusion Detection

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A Combination Classification Method of Multiple Decisions Trees-based on generic algorithm towards Customer Behavior

A Combination Classification Method of Multiple Decisions Tr...

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15th International Conference on Management Science and Engineering

作者： Cui Xiao-jian Tong Wei-min Li Yi-jun Harbin Inst Technol Sch Management Harbin 150001 Peoples R China China Finan Futures Exchange Dalian 200122 Peoples R China

ISBN: (纸本)9781424423873

In order to solve the classification problems of customer behaviors with randomicity and non-conformability, a combination classification method is proposed of multiple decision trees based on genetic algorithm. In this method, multiple decision trees that adopt the method of probability measurement level output are combined in parallel. Genetic algorithm is utilized to optimize connection weight matrix in combination algorithm. Furthermore, two sets of simulation experiment data are used to test and evaluate the proposed method. Results of the experiments indicate that the proposed method generates a higher classification accuracy rate than other methods' for customer behavior segmentation.

关键词： customer behaviors classification decision trees generic algorithm

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Evaluation of Car-following Models Using Trajectory Data from Real Traffic

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Procedia - Social and Behavioral Sciences 2012年 43卷 356-366页

作者： Jian Zheng Koji Suzuki Motohiro Fujita Graduate School of Engineering Nagoya Institute of Technology

In order to achieve a complete insight in the state-of-the-art of traffic modelling, several typical car-following models are evaluated by using trajectory data from real traffic conditions and genetic-algorithm-based calibration method in this study. The models with calibrated parameters are validated not only under uncongested traffic conditions but also under congested traffic conditions. Unlike the results in previous study based on experimental data, there are obvious differences in the performance of these models. Models with more parameters produce relatively lower error rate in calibration process but over-fitting problem appears in validation process. The model very popular in the physical community is found not suitable for real traffic simulation, although it can represent some traffic phenomena under certain condition. Even with simple rules and discrete variables, cellular automata model achieves satisfactory simulation results both in calibration and validation process. Besides, it is also noteworthy that all of the models perform rather worse in validation process than in calibration process. Using different parameters or even different models under different traffic conditions seems to be feasible for depicting real traffic more accurately.

关键词： Car-following model Traffic simulation generic algorithm

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Trap system based on generic algorithm

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Nanjing Youdian Daxue Xuebao (Ziran Kexue Ban)/Journal of Nanjing University of Posts and Telecommunications (Natural Science) 2008年第6期28卷 50-55页

作者： Gong, Jing Sun, Zhi-Xin Xu, Hong-Xia College of Mathematics and Physics Nanjing University of Posts and Telecommunications Nanjing 210003 China Institute of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Ltd. Beijing 100006 China

Intrusion deception system is one kind network safety method. When a system is intruded, it can set a controllable attack circumstance, so it can capture intrusion information as much as possible. Based on these information, we can analyze intrusion action, and prevent farther hostility destroy, there fore we can protect network more effectively. This paper introduces a kind of trap system based on generic algorithm, whose key technologies include hidden data catch technology and behavior analysis technology based on generic algorithm. Experiments prove the system can capture hostility behavior, and defense some new attacks.

关键词： Behavior analysis Data capture generic algorithm Honeypot

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Heuristic algorithms for the cardinality constrained efficient frontier

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2011年第3期213卷 538-550页

作者： Woodside-Oriakhi, M. Lucas, C. Beasley, J. E. Brunel Univ CARISMA Uxbridge UB8 3PH Middx England

This paper examines the application of genetic algorithm, tabu search and simulated annealing metaheuristic approaches to finding the cardinality constrained efficient frontier that arises in financial portfolio optimisation. We consider the mean-variance model of Markowitz as extended to include the discrete restrictions of buy-in thresholds and cardinality constraints. Computational results are reported for publicly available data sets drawn from seven major market indices involving up to 1318 assets. Our results are compared with previous results given in the literature illustrating the effectiveness of the proposed metaheuristics in terms of solution quality and computation time. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Efficient frontier generic algorithm Portfolio optimisation Simulated annealing Tabu search

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Cooperative route plan of initial stage for multiple missiles formation

Cooperative route plan of initial stage for multiple missile...

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23rd Chinese Control and Decision Conference

作者： Sun, J. Bao, Y. M. Wu, S. T. Beijing Univ Aeronaut & Astronaut Automat Sci & Elect Engn Sch Beijing 100083 Peoples R China

ISBN: (纸本)9781424487363

Cooperative task implement of multiple aircraft is a basic character of modern aircraft application. It highly makes requirement of task assignment and route plan. Task assignment is precondition of route plan, which can alleviate pressure of route plan in the sequel, so it can be seen as initial extension of route plan. To solve problem of task assignment and route plan of multiple missiles between land launch and mid-guidance switch, the integrated method of generic algorithm (GA) and dynamic program (DP) is presented. The software of route plan for multiple missiles of initial stage is developed. Use of the software shows engineering effectiveness of this integrated method.

关键词： Route plan generic algorithm Dynamic Plan Task assignment

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LRGA for Solving Profit based Generation Scheduling Problem in Competitive Environment

LRGA for Solving Profit based Generation Scheduling Problem ...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Logenthiran, T. Srinivasan, Dipti Natl Univ Singapore Dept Elect & Comp Engn Singapore 117548 Singapore

ISBN: (纸本)9781424478354

Deregulated power industries increase the efficiency of electricity production and distribution, and offer higher quality, secure, and more reliable electricity at low prices. In a deregulated environment, utilities are not required to meet the total load demand. Generation companies (GENCOs) schedule the generators that produce less than the predicted load demand and reserve, but aim to deliver maximum profits. The scheduling of generators depends on the market price. More number of generating units are committed when the market price is higher. When more number of generating units are brought in the deregulated market, more profit can be achieved by producing higher amount of power. This paper present a hybrid algorithm to solve a profit based unit commitment problem in a deregulated environment. The proposed algorithm has been developed from generation company's point of view. It maximizes the profit of the generation company in the deregulated power and reserve markets. A hybrid methodology between Lagrangian Relaxation and generic algorithm (LRGA) is used to solve generation scheduling in a day-ahead competitive electricity market. The results obtained are quite encouraging and useful in deregulated market optimization.

关键词： Profit-based unit commitment Regulated power system Lagrangian relaxation generic algorithm Generation scheduling

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A New Hybrid Genetic K-means Clustering algorithm

A New Hybrid Genetic K-means Clustering algorithm

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2011 4th IEEE International Conference on Computer Science and Information Technology(ICCSIT 2011)

作者： WU Xian Faculty of Software Fujian Normal University Fuzhou,China Chen Xue-xiong Department of Computer Science and Technology Nanjing University Nanjing,China

Recently,intelligent algorithm based K-Means clustering algorithm proposed by many researchers for the respective advantages of clustering algorithm and computational *** paper present a genetic K-Means algorithm combined with simulated *** method hinges on the use of simulated annealing to perform a density estimation of the data at various locations for algorithm initialisation,and it's easy to change parameters in real time while generating various start *** analysis and experimental results show that our hybrid algorithm has better clustering quality and general performance.

关键词： Clustering K-means algorithm generic algorithm simulated annealing

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