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5th IET International Conference on Clean Energy and Technology (CEAT2018)

作者： Normazlina Mat Isa Tan Chee Wei Abd Halim Mohd Yatim Jabatan Kejuruteraan Elektrik Politeknik Merlimau 71300 Merlimau Melaka School of Electrical Engineering Faculty Kejuruteraan Universiti Teknologi Malaysia 81310 Skudai Johor

Cogeneration is one of the microgrid implementation that is able to provide both electricity and heat energy simultaneously. Thus, it have been variously utilized in many energy generation plant including the commercial buildings like airport, hospital and hotel. However, a sophisticated control system is needed to ensure the objective of power flow in meeting the load requirement can be achieved. Energy management system which laid on the top of control hierarchy seems to have the ability to control and manage the energy flow in many type of microgrid especially cogeneration system. This presented article discuss a method of energy management system for the hybrid cogeneration system using the optimization approach. The objective of this proposed energy management system based optimization is to reduce the operational cost of hybrid cogeneration system that consist of PEMFC, photovoltaic and battery. Considering the parameters and variables such as weather conditions, load profile and fuel price, the optimization formulation is solved using the Harmony Search algorithm which subjected to recognice constraints. Results of this study is leading to give the look up table which represent the generated power of each energy resources in 24 hours interval time. The simulation and analysis is performed in MATLAB/SIMULINK environment.

关键词： Energy management systems searching algorithm Cogeneration Power production energy exchange Energy flow Energy sources control hierarchy commercial buildings Thermal energy Power flow

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Automatic Image Enhancement Using Evolutionary Optimization algorithms

Automatic Image Enhancement Using Evolutionary Optimization ...

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IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology

作者： Varun Saxena Deeksha Goel Tarun Kumar Rawat Electronics and Communication Engineering Division Netaji Subhas Institute of Technology

ISBN: (数字)9781538624401

ISBN: (纸本)9781538624418

This paper presents a novel method of improving image quality using meta-heuristic algorithms such as Bat algorithm, Cuckoo Search algorithm and Interior Search algorithm by contrast enhancement method. The performance of these algorithms are compared based on their ability to enhance the contrast, detail and sharpness of the gray scale image. These algorithms are used to generate optimal parameters to reach the global best of a fitness function which is then used to judge the enhancement achieved for the given image.

关键词： Image enhancement Cuckoo search algorithm Bat algorithm Interior search algorithm Hybrid intelligent optimization image enhancement searching algorithm Optimization algorithms contrast enhancement method Meta-heuristic algorithms Image quality algorithms optimal parameter Sharpness

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A Method of Channel Capacity Optimization Based on Dynamically Adjusted Inertia Weight Acceleration Factor in Cognitive Sensing Network

A Method of Channel Capacity Optimization Based on Dynamical...

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International Conference on Software Engineering Research, Management and Applications (SERA)

作者： Yanjun Hu Dongdong Wei Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538658871

The optimization of channel capacity in cognitive sensor networks is a complicated optimization problem. The traditional gradient search method based on the analysis has more restrictions on the objective function, and high complexity, and can not determine the convergence. Aiming at the inherent problems of the traditional gradient search algorithm, the particle swarm optimization(PSO) with simple and easy to implement, distributed computing and fast convergence speed can be used to solve the problem of channel capacity optimization. It is difficult to balance the global search with the local search by adopting a standard particle swarm algorithm with fixed algorithm parameters, which can not solve the premature convergence problem that may occur. The specific meaning of each parameter of the algorithm is analyzed in this paper, and an improved particle swarm optimization algorithm based on dynamic adjustment of inertia weight acceleration factor(DWAPSO) is proposed, and the improved particle swarm optimization algorithm is applied to the optimization of channel capacity in cognitive sensor networks. The simulation results show that the improved channel capacity optimization algorithm(DWAPSO-CA) can speed up the convergence rate, increase the system capacity and get a lower bit error rate.

关键词： Channel capacity particle swarm algorithm Bit error rate system capacity Particle swarm optimization Inertial forces speedup factor Search methods searching algorithm Converge Distributed computing

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An Efficient Dynamic Ridesharing algorithm 17

An Efficient Dynamic Ridesharing Algorithm

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17th IEEE International Conference on Computer and Information Technology (CIT) / IEEE Int Workshop on Secure and Resource-Efficient Edge Computing (SecureEdge) / IEEE Int Symposium on Recent Advances of Computer and Information Technologies (RACIT)

作者： Gao, Jianren Wang, Yuxin Tang, Haoyang Yin, Zhao Ni, Lei Shen, Yanming Dalian Univ Technol Sch Comp Sci & Technol Dalian Peoples R China

ISBN: (纸本)9781538609583

In this paper, we propose a scheduling algorithm for ridesharing. It efficiently serves real-time requests sent by passengers and generates ride sharing schedules that try to meet users' demands. In our method, we first propose a taxi searching algorithm using binary search strategy to quickly and efficiently retrieve candidate taxis that are likely to satisfy a trip request. A scheduling algorithm is then proposed. It checks each candidate taxi and insert the request trip into the schedule of the taxi which satisfies the request with the maximum average satisfaction. We evaluated our system using a large scale taxi dataset containing 101,952 trips in Beijing Chaoyang district. Results showed that our approach serves 40% additional taxi users while saving 30% travel distance compared with no-ridesharing.

关键词： ridesharing searching algorithm scheduling algorithm

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Research on the Surakarta chess game program based on Unity 3D 29

Research on the Surakarta chess game program based on Unity ...

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第29届中国控制与决策会议

作者： Wang LinLin Wu YuNu Wang YaJie Cao Guoqiang Engineering Training Center Shenyang Aerospace University

ISBN: (纸本)9781509046584

Surakarta chess is researched with the computer game technology,which is a kind of computer chess game in the complete information *** order to increasing the human-computer interaction of the computer games system,the representing method of chessboard with 3 D form is studied by use of unity 3 D game engine *** Surakarta game system is designed using VC++ *** this system,the Monte Carlo Tree Search(MCTS) algorithm and Minimax algorithm are used *** system has improve the visual effect,and combining two searching algorithm is feasibility.

关键词： computer games Surakarta Unity 3D searching algorithm

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Comparison of two types of Quantum Oracles based on Grover's Adaptative Search algorithm for Multiobjective Optimization Problems

Comparison of two types of Quantum Oracles based on Grover's...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Fogel, Gerardo G. Baran, Benjamin Villagra, Marcos Natl Univ Asuncion Asuncion Paraguay

ISBN: (纸本)9788394625375

Quantum Computing is a field of study in computer science based on the laws of quantum physics. Quantum computing is an attractive subject considering that quantum algorithms proved to be more efficient than classical algorithms and the advent of large-scale quantum computation. In particular, Grover's search algorithm is a quantum algorithm that is asymptotically faster than any classical search algorithm and it is relevant for the design of fast optimization algorithms. This article proposes two algorithms based on Grover's adaptative search for biobjective optimization problems where access to the objective functions is given via two different quantum oracles. The proposed algorithms, considering both types of oracles, are compared against NSGA-II, a highly cited multiobjective optimization evolutionary algorithm. Experimental evidence suggests that the quantum optimization methods proposed in this work are at least as effective as NSGA-II in average, considering an equal number of executions. Experimental results showed which oracle required less iterations for similar effectiveness.

关键词： Quantum computing Optimization Linear programming algorithm design and analysis Boolean functions Search problems Electronic mail quantum computing algorithm design and analysis tabu search electronic mail searching algorithm Boolean functions linear programming algorithms quanta

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Scalable Parallel Distributed Coprocessor System for Graph searching Problems with Massive Data

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SCIENTIFIC PROGRAMMING 2017年第Pt.2期2017卷 1-9页

作者： Huang, Wanrong Yi, Xiaodong Sun, Yichun Liu, Yingwen Ye, Shuai Liu, Hengzhu Natl Univ Def Technol Sch Comp Deya Rd 109 Changsha 410073 Hunan Peoples R China

The Internet applications, such as network searching, electronic commerce, and modern medical applications, produce and process massive data. Considerable data parallelism exists in computation processes of data-intensive applications. A traversal algorithm, breadth-first search (BFS), is fundamental in many graph processing applications and metrics when a graph grows in scale. A variety of scientific programming methods have been proposed for accelerating and parallelizing BFS because of the poor temporal and spatial locality caused by inherent irregular memory access patterns. However, new parallel hardware could provide better improvement for scientific methods. To address small-world graph problems, we propose a scalable and novel field-programmable gate array-based heterogeneous multicore system for scientific programming. The core is multithread for streaming processing. And the communication network InfiniBand is adopted for scalability. We design a binary search algorithm to address mapping to unify all processor addresses. Within the limits permitted by the Graph500 test bench after 1D parallel hybrid BFS algorithm testing, our 8-core and 8-thread-per-core system achieved superior performance and efficiency compared with the prior work under the same degree of parallelism. Our system is efficient not as a special acceleration unit but as a processor platform that deals with graph searching applications.

关键词： PROCESSOR parallelism electronic commerce acceleration Coprocessors spatial locality STREAMS(PROCESS) data parallel Scalability searching algorithm Parallel Lines

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Decomposition algorithm of searching equilibria in a dynamic game

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AUTOMATION AND REMOTE CONTROL 2015年第10期76卷 1865-1893页

作者： Krasovskii, N. A. Tarasyev, A. M. Russian Acad Sci Inst Math & Mech Ural Branch Ekaterinburg Russia

This paper considers a noncooperative game of several players (governments of neighboring countries) participating in emission reduction trading. A special emphasis is placed on the case of two players, one representing Eastern European countries and the other being the countries of the former Soviet Union. We perform statistical analysis of the model parameters based on real data under quadratic cost functions and logarithmic utility functions. The concepts of a noncooperative Nash equilibrium and cooperative Pareto maxima are introduced and connections between them are established. A new concept, i.e., a market equilibrium, which combines the properties of Nash and Pareto equilibria, is rigorously defined. An analytical solution of the market equilibrium problem is given. This analytical solution can serve for verification of numerical search algorithms. In addition, we propose a computational algorithm of market equilibrium search, which shifts a competitive Nash equilibrium to a cooperative Pareto maximum. The algorithm is interpreted as a repeated auction, where the auctioneer possesses no information about the cost functions and the functions of environmental effect from emission reduction of the participating countries. An auctioneer strategy leading to market equilibrium attainment is considered. From the game-theoretic viewpoint, a repeated auction describes a learning process in a noncooperative repeated game under uncertainty. We compare the results gained by the proposed computational algorithms with their analytical counterparts. And finally, numerical calculations of equilibrium and algorithm trajectories converging to the equilibrium are demonstrated.

关键词： supply balance emission reduction ANALYTICAL SOLUTION Auctioneers model parameters Cost functions algorithms Players searching algorithm Learning processes Nash equilibrium Commonwealth of Independent States environmental effects

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A Modified Harmony Search algorithm for Solving the Dynamic Vehicle Routing Problem with Time Windows

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SCIENTIFIC PROGRAMMING 2017年第Pt.2期2017卷 1-13页

作者： Chen, Shifeng Chen, Rong Gao, Jian Dalian Maritime Univ Dept Informat Sci & Technol Dalian 116026 Peoples R China

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion;however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers' requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.

关键词： VND Hydrogen Sulfide (H2S3) Routing Problem Heuristic algorithms algorithms searching algorithm Time windows Vehicle routing

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The Design and Optimization of GaAs Single Solar Cells Using the Genetic algorithm and Silvaco ATLAS

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INTERNATIONAL JOURNAL OF PHOTOENERGY 2017年第Pt.2期2017卷 1-7页

作者： Attari, Kamal Amhaimar, Lahcen El Yaakoubi, Ali Asselman, Adel Bassou, Mounir Abdelmalek Essaadi Univ Opt & Photon Team Fac Sci Tetouan Morocco

Single-junction solar cells are the most available in the market and the most simple in terms of the realization and fabrication comparing to the other solar devices. However, these single-junction solar cells need more development and optimization for higher conversion efficiency. In addition to the doping densities and compromises between different layers and their best thickness value, the choice of the materials is also an important factor on improving the efficiency. In this paper, an efficient single-junction solar cell model of GaAs is presented and optimized. In the first step, an initial model was simulated and then the results were processed by an algorithm code. In this work, the proposed optimization method is a genetic search algorithm implemented in Matlab receiving ATLAS data to generate an optimum output power solar cell. Other performance parameters such as photogeneration rates, external quantum efficiency (EQE), and internal quantum efficiency (EQI) are also obtained. The simulation shows that the proposed method provides significant conversion efficiency improvement of 29.7% under AM1.5G illumination. The other results were J(sc) = 34.79 mA/cm(2), V-oc = 1 V, and fill factor (FF) = 85%.

关键词： solar cells gallium arsenides searching algorithm simulating Conversion efficiency Solar equipment optimization method Genetic algorithm (GA) characteristic parameter

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