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Classification of hyperspectral remote sensing images based on simulated annealing genetic algorithm and multiple instance learning

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Journal of Central South University 2014年第1期21卷 262-271页

作者：高红民周惠徐立中石爱业 College of Computer and Information Engineering Hohai University College of Computer and Software Nanjing Institute of Industry Technology

A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.

关键词： hyperspectral remote sensing images simulated annealing genetic algorithm support vector machine band selection multiple instance learning

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MULTI-AXLE MOVING TRAIN LOADS IDENTIFICATION ON SIMPLY SUPPORTED BRIDGE BY USING simulated annealing genetic algorithm

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INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS 2011年第1期11卷 57-71页

作者： Qu, Weilian Wang, Yi Pi, Yonglin Wuhan Univ Technol Hubei Key Lab Roadway Bridge & Struct Engn Wuhan 430070 Peoples R China Univ New S Wales Sch Civil & Environm Engn Ctr Infrastruct Engn & Safety Sydney NSW 2052 Australia

Identification of multi-axle moving train loads is very important for the bridge design, construction, and maintenance. This paper presents an optimization method for identification of multi-axle moving train loads on bridges, which minimizes differences between the measured deflections and the deflections reconstructed from the identified moving loads and has the merits of both the global searching properties of genetic algorithms and the local searching properties of simulated annealing algorithms. Effects of algorithm parameters and of bridge-train system parameters on the robustness and accuracy of the proposed method are investigated. The results show that the method is feasible, accurate, and effective for multi-axle moving train loads identification.

关键词： Multi-axle moving train loads load identification simulated annealing genetic algorithm

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Optimal control of cobalt crust seabedmining parameters based on simulated annealing genetic algorithm

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Journal of Central South University 2011年第3期18卷 650-657页

作者：夏毅敏张刚强聂四军卜英勇张振华 School of Mechanical and Electrical Engineering Central South University Guangxi Liugong Machinery Co.Ltd

Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.

关键词： cobalt crust mining parameter specific energy consumption simulated annealing genetic algorithm

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Surface/Surface Intersection Using simulated annealing genetic algorithm

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High Technology Letters 2000年第4期6卷 39-45页

作者：唐敏 Zhejiang Univ Hangzhou China

The genetic algorithm and marching method are integrated into a novel algorithm to solve the surface intersection problem. By combining genetic algorithm with local searching method the efficiency of evolution is greatly improved. By fully utilizing the global searching ability and instinct attribute for parallel computation of genetic algorithm and the local rapid convergency of marching method, the algorithm can compute the intersection robustly and generate correct topology of intersection curves. The details of the new algorithm are discussed here.

关键词： Surface intersection Marching method simulated annealing genetic algorithm

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Solving the TSP by simulated annealing genetic algorithm Based on Google Maps JavaScript API

Solving the TSP by Simulated Annealing Genetic Algorithm Bas...

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2nd International Conference on Manufacturing Science and Engineering

作者： He, Xinbiao Mo, Yiwei Guangxi Univ Mech Engn Coll Nanning 530004 Peoples R China

ISBN: (纸本)9783037850398

Google Maps Java Script API enable users calculate directions by using the Directions Service object. With these directions results, a new approach to solve the Travelling Salesman Problem (TSP) is proposed in this paper. This Directions Service object communicates with the Google Maps API which receives directions requests and returns computed results. TSP is solved by simulated annealing genetic algorithm (SAGA) with help of returned directions results. In experiment example, the optimal route of the TSP was provided graphically with Google Maps and textually in user interface. The final results demonstrated the feasibility of the proposed approach.

关键词： Google Maps JavaScript API TSP simulated annealing genetic algorithm

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Analysis on factors affecting the employment of landless peasants based on simulated annealing genetic algorithm

Analysis on factors affecting the employment of landless pea...

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International Forum on Materials Processing Technology (IFMPT) / International Conference on Sensors, Instrument and Information Technology (ICSIIT)

作者： Zhu, Zhonghao Hohai Univ Sch Business Nanjing 211100 Jiangsu Peoples R China

ISBN: (纸本)9783038350453

In national plan of twelfth five-year, orchestrating city-country development and accelerating process of urbanization will be one of the leading strategies. Large areas of farmland turn to non-agricultural irreversibly in the process of accelerating urbanization, the existing land expropriation system running by planned economic system damage farmers' rights and incomes. Therefore, as vulnerable groups, landless peasants' employments need more concern. The study takes Zhenjiang city for an example, proposes a factor selecting method based on the simulated annealing genetic algorithm (SAGA). The factor selecting method is proposed from each subspace, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Experimental results show that achieving a significant increase in the employment rate is possible using SAGA obtained from the proposed approach.

关键词： landless peasants simulated annealing genetic algorithm employment factor selecting

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Ground Robot Path Planning based on simulated annealing genetic algorithm 10

Ground Robot Path Planning based on Simulated Annealing Gene...

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10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Wang, Lanfei Guo, Jun Wang, Qu Kan, Jiangming Beijing Univ Posts & Telecommun Informat & Commun Engn Inst Beijing Peoples R China Beijing Forestry Univ Engn Inst Beijing Peoples R China

ISBN: (数字)9781728109749

ISBN: (纸本)9781728109749

Robot path planning is the key to robot navigation. We implemented the robot path planning based on ant colony algorithm and genetic algorithm, and proposed simulated annealing genetic algorithm. Under the condition that there is not much difference in running time (within 3 seconds), planning results of different terrains, start and end points based on ant colony algorithm(with 200 iterations)and simulated annealing genetic algorithm show that, the optimal path outputted by simulated annealing genetic algorithm is better than the optimal path outputted by ant colony algorithm in terms of avoiding obstacles;The simulated annealing genetic algorithm has shorter average optimal path length than ant colony algorithm in multiple tests, the average path length is reduced by 6.85%.

关键词： robot path planning ant colony algorithm simulated annealing genetic algorithm 3D environment

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A simulated annealing genetic algorithm for Urban Power Grid Partitioning Based on Load Characteristics

A Simulated Annealing Genetic Algorithm for Urban Power Grid...

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International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Xin, Xiao Li, Ke-Jun Sun, Kaiqi Liu, Zhijie Wang, Zhuo-di Shandong Univ Dept Elect Engn Jinan 250061 Shandong Peoples R China

ISBN: (纸本)9781728144634

Power network partitioning is an old but still challenging and meaningful problem. A large power grid is divided into several zones so that buses within zones are electrically close. Urban power grid partitioning is usually ignored due to its scale is smaller than large power grid partitioning. This paper proposes a method that considers the characteristics of urban loads and a hybridization of genetic algorithm with simulated annealing algorithm is applied to get the best scheme for network partitioning problems. The optimal number of partitions is determined by related theories of matrix analysis and the candidate solutions are evaluated by a multi-index fitness function based on the electrical distance matrix. This method is applied to a real urban power grid with 134 buses. The short circuit currents before and after partitioning are compared to test the validity and practicability of this method.

关键词： Urban power grid network partitioning load characteristics simulated annealing genetic algorithm

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An Improved Adaptive Scheduling Strategy Utilizing simulated annealing genetic algorithm for Data Center Networks

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2017年第11期11卷 5243-5263页

作者： Wang, Wentao Wang, Lingxia Zheng, Fang South Cent Univ Nationalities Coll Comp Sci Wuhan 430074 Hubei Peoples R China

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

关键词： scheduling adaptive methods simulated annealing genetic algorithm software defined network data center

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Applications of simulated annealing genetic algorithm to Emotion Recognition from Physiological Signals

Applications of Simulated Annealing Genetic Algorithm to Emo...

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2010 International Conference on Computer,Mechatronics, Control and Electronic Engineering (CMCE 2010)

作者： Lianzhe Zhou school of Computer Science and Engineering Changchun university of technology Changchun,China Huanli Pang school of Computer Science and Engineering Changchun university of technology Changchun,China Hanmei Liu school of Computer Science and Engineering Changchun university of technology Changchun,China Wei Xiao school of Computer Science and Engineering Changchun university of technology Changchun,China

Emotion recognition is one of the most important issues in advanced human-computer interaction *** paper proposes The simulated annealing genetic algorithm to recognizing four emotional states from four physiological ... 详细信息

关键词： Emotion Recognition simulated annealing genetic algorithm Physiological Signals.

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