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Development of optimal integrated renewable energy model with battery storage for a remote Indian area

ENERGY 2016年第0期111卷 803-817页

作者： Rajanna, S. Saini, R. P. Indian Inst Technol Alternate Hydro Energy Ctr Roorkee 247667 Uttar Pradesh India

Over the past few years, renewable energy has come to be seen as a possible solution to the energy problems of people. The present work focuses on optimal sizing of an integrated renewable energy system (IRES) considering locally available different renewable energy sources namely micro hydro, solar, wind, biomass and biogas with battery system for electrification of a remote area in Karnataka state in India. Genetic algorithm (GA) has been used to minimize the total net present cost (TNPC) and cost of energy (COE) of the developed IRES model considering the three decision variables-total active sunshine area occupied by the SPV modules, total swept area required to install wind mills and state of charge (SOC) of battery system. Scenario based results of optimal sizes, TNPC and COE have been obtained based on suitable device types and time schedule of biomass generator. Based on optimization results, three IRE scenarios are proposed for the study area. Of the three, scenario-S1 for zone 2 and zone 3. While, scenario-S2 for zone 1 and zone 4 are found to be most feasible for the study area. Further, optimal time schedule, resource combination and device type for all zones have also been determined. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Net present cost (NPC) generic algorithm Integrated renewable energy optimization model (IREOM) Remote area electrification

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Predictive capability evaluation of RSM, ANFIS and ANN: A case of reduction of high free fatty acid of palm kernel oil via esterification process

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ENERGY CONVERSION AND MANAGEMENT 2016年第0期124卷 219-230页

作者： Betiku, Eriola Odude, Victoria O. Ishola, Niyi B. Bamimore, Ayorinde Osunleke, Ajiboye S. Okeleye, Adebisi A. Obafemi Awolowo Univ Dept Chem Engn Biochem Engn Lab Ife 220005 Osun State Nigeria Obafemi Awolowo Univ Dept Chem Engn Proc Syst Engn Lab Ife 220005 Osun State Nigeria

Response surface methodology (RSM), adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) were tested in the modeling of acid pretreatment of palm kernel oil with a very high acid value (22 +/- 0.1 mg KOH/g oil). This was investigated considering methanol/oil molar ratio (1.3:1-3.8:1), catalyst loading (0.3-0.5 vol.%) and time (20-40 min) using Box Behnken design. The developed RSM, ANFIS and ANN models described the process with high accuracy (coefficient of determination, R-2>0.99 and average absolute deviation, AAD = 2.72-23.96%). RSM, RSM coupled with generic algorithm (GA), ANFIS-GA and ANN-GA were applied to optimize the process for best operating condition and ANN GA gave the minimum acid value (0.64 mg KOH/g) under the best optimal condition of methanol/oil molar ratio 3.4:1, catalyst loading 0.39 vol.% and time 24.06 min. Based on the statistical indices obtained, RSM performed the least, while ANN marginally outperformed ANFIS. GA proved to be superior to RSM in the optimization of the esterification process. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Esterification Adaptive neuro-fuzzy inference system Artificial neural network Response surface methodology generic algorithm

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generic case complexity of the Graph Isomorphism Problem

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GROUPS COMPLEXITY CRYPTOLOGY 2016年第1期8卷 9-20页

作者： Noskov, Gennady A. Rybalov, Alexander N. Russian Acad Sci Sobolev Inst Math Siberian Branch Omsk Russia Omsk State Tech Univ Omsk Russia

The edge test is a partial algorithm for the Graph Isomorphism Problem based on comparison the number of edges. We perform a probabilistic analysis of the efficiency of the edge test. With the binomial distribution B(n, p) on the set of inputs, we estimate the asymptotic failure probability of the edge test depending on the rate of decay of parameter p. In particular, if p <= 1/2, np -> lambda > 0, then the asymptotic failure probability is nonzero, so that the edge test does not solve generically the Graph Isomorphism Problem. On the other hand, if p <= 1/2, np -> infinity, then the failure set is negligible and the edge test generically solves the Graph Isomorphism Problem in polynomial time.

关键词： Graph isomorphism binomial random graph Poisson distribution Legendre polynomial generic algorithm

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An Efficient Interpolation-Based Projected Sum of Product Decomposition via Genetic algorithm

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JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING 2016年第1期27卷 1-19页

作者： Chen, Tai-Lin Wang, Chun-Yao Huang, Ching-Yi Chen, Yung-Chih Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300 Taiwan Yuan Ze Univ Dept Comp Sci & Engn Chungli 320 Taiwan

Projected Sum of Products (P-SOP) is a bounded multi-level representation. The synthesis of P-SOP representation is based on decomposing the input space with respect to the orthogonal basis x(i)'circle plus p(X-(i)) and x(i)circle plus p(X-(i)) where x(i) is an input variable and p(X-(i)) is a function of all variables except x(i). Different p(X-(i)) may result in different areas after synthesis. Therefore, to obtain a minimal P-SOP circuit, it is important to select an appropriate variable xi and function p((X(i))). In this paper, we propose a Genetic algorithm to efficiently determine x(i) and p(X-(i)). Experimental results show that the proposed approach saves 81% CPU time in searching such a pair as compared to an exhaustive method without sacrificing the optimality.

关键词： Logic synthesis interpolation optimization EX-OR network generic algorithm functional decomposition

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Test Configuration for Incipient Fault Detection

Test Configuration for Incipient Fault Detection

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2016 2nd International Conference on Electronics,Network and Computer Engineering(ICENCE 2016)

作者： Shuming Yang Xiaoyu Wen Xiaofei Zhang College of Basic Education National University of Defense Technology

Information sensing and test are premise and foundation of(Equipment Health Management, EHM), a reasonable sensor configuration not only provide accurate and complete fault information, but also improve fault diagnostics, fault prognostics and health state evaluation capability. To address the problem that the traditional test selection and optimization are mainly for fault detection and isolation, then, testability indices for EHM are firstly formulated quantitatively, then, test optimization selection model which minimizes test cost is modeled, and the generic algorithm is introduced to solve the problem. At last, a simulation case and an application case are given to verify & validate the proposed model and method.

关键词： Equipment Health Management Design for Testability Test Optimization Configuration generic algorithm

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A Chance-Constrained Programming Model for Medical Resources Order and Distribution Scheduling Based on Time-Space Network

A Chance-Constrained Programming Model for Medical Resources...

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International Conference on Logistics, Informatics and Service Sciences (LISS)

作者： Zhang, Huixiang Liu, Ming Nanjing Univ Sci & Technol Dept Management Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781479918911

This paper studies the medical resources order and distribution scheduling problem with stochastic demand. A chance-constrained programming model is proposed based on time-space network with the objective of minimizing the hospital's total operating costs. generic algorithm is employed to solve the optimization model. The numerical test results show the good performance of the proposed method.

关键词： time-space network medical resources chance-constrained programming generic algorithm

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Cost-efficient Divisible Load Scheduling using Genetic algorithm 11

Cost-efficient Divisible Load Scheduling using Genetic Algor...

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11th International Conference on Computational Intelligence and Security (CIS)

作者： Xuan, Hejun Wang, Yuping Hao, Shanshan Wang, Xiaoli Xidian Univ Sch Comp Sci & technol Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9781467386609

In the past decades, divisible load scheduling has become an increasingly concerned field in the research of computer science. At the same time, the total system cost of data center has received worldwide attention, and the concept of green computing has been put forward. This paper investigates an cost-efficient divisible load scheduling using genetic algorithm. It focuses on finding an efficient scheduling strategy for distributed environment so that the total system cost is minimum. First, the system cost model is established when the start overheads are considered. Second, the optimization model has a time constraints for the sake of the makespan can be tolerant for the user. Third, a novel and efficient generic algorithm is proposed. Finally, the experimental results demonstrate that the the proposed algorithm performs well.

关键词： divisible load scheduling total system cost makespan generic algorithm

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Research Reconfiguration Method for Warship Power System Based on Graph Trace Analysis and generic algorithms

Research Reconfiguration Method for Warship Power System Bas...

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International Conference on Advanced Engineering Materials and Architecture Science (ICAEMAS 2014)

作者： Shang, Anli Xia, Li Wang, Zheng Naval Univ Engn Wuhan 430033 Hubei Province Peoples R China

ISBN: (纸本)9783037859766

The electric power network reconfiguration of warship integrated power system is one of the most important methods to restore power supply and improve survivability of shipboards under fault. The reconfiguration method based on graph trace analysis (GTA) and generic algorithms is proposed for warship integrated power system in order to maximize the number of served loads with highest priority under fault. Simulation results have demonstrated that is method is able to reach target configurations.

关键词： Graph Trace Analysis generic algorithm Reconfiguration Integrated Power System

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Game Model of Taxi Service Pricing Based on Deregulation 5

Game Model of Taxi Service Pricing Based on Deregulation

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5th International Conference on Transportation Engineering, ICTE 2015

作者： Hu, Ji Hu, Wanxin Hu, Yiwei Liu, Yan Jiang, Jinyao College of Traffic and Logistics Southwest Jiaotong University Chengdu China National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu China Wuhan Railway Vocational College of Technology Wuhan China China Railway Siyuan Survey and Design Group Co. Ltd Wuhan China Urban and Rural Planning and Design Institute of YuLin Yulin Guangxi China

ISBN: (数字)9780784479384

ISBN: (纸本)9780784479384

This thesis, based on the characteristics of the taxi industry, to investigate the game model of pricing the taxi industry in relax regulation conditions. By analyzing the relationship, establish in Stackelberg bi-level programming model. Among them, the upper programming for the maximization of social welfare, lower planning is to maximize the interests of Taxi Company. The model considered the taxi operation of actual loading mileage. Considering the solving of bi-level programming model is complex, this Article uses genetic algorithm to solve the upper limit value after relax regulation Then combining case, the pricing game model is studied. The calculation shows that the model can effectively respond to the pricing process. At the same time, the algorithms can effective computational models. © ASCE.

关键词： Transportation economy Pricing model Bi-level programming Taxi regulation generic algorithm Taxi Public Transportation Pricing deregulation Taxi services Hunting Game theory Game animals limits (mathematics) operator level routine Programming

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A Parallelization Method of Genetic algorithms for Optimal Design of Microwave Filter

A Parallelization Method of Genetic Algorithms for Optimal D...

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IEEE International Workshop on Electromagnetics (IEEE iWEM) - Applications and Student Innovation Competition

作者： Otani, Hajime Yamaguchi, Shoichi Maeda, Yuji Omiya, Manabu Hokkaido Univ Grad Sch Informat Sci & Technol Kita Ku Kita 14Nishi 9 Sapporo Hokkaido Japan Hokkaido Univ Informat Initiat Ctr Kita Ku Sapporo Hokkaido Japan

ISBN: (纸本)9781479948154

The evolutional computing including generic algorithms (GAs) is applied to automatic design optimization in many practical problems. Using the method, we can find an optimum or a quasi optimum solution automatically, and may reduce the computational complexity about several to ten percent compared with the full searching in the parameter space. In general, an evaluation of fitness takes much time to be calculated. So it is necessary to speed up calculations by a parallel processing technique. In this paper, we discuss to employ two kinds of genetic algorithm (GA), parameter-free GA and micro-GA, for an automatic design optimization of dichroic band pass filter operating in the millimeter to terahertz frequency band. And their parallelization methods are proposed and compared with each other on the degree of acceleration. Electromagnetic simulations of dichroic filter are carried out using the FDTD technique.

关键词： evolutionary computing generic algorithm dichroic filter automatic and optimal design FDTD technique parallel processing

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