Grasping the effect of power supply net capacity on electricity sales has a great significance to analyze the trend of electricity sales accurately. Based on correlation analysis of historical data of the first, second, third industrial and residential electricity sales and power supply net capacity of power company, this paper presents a method of analyzing the effect of power supply net capacity on electricity sales by growth curve. The method eliminates the effect of seasonal factor and random factor of power supply net capacity and electricity sales by X13 seasonal adjustment, calculates the leading time of power supply net capacity ahead of electricity sales by dynamic time warping, calculates load operation ratio of power supply net capacity by growth curve. The method is used for quantitative analysis in studying electricity sales' changes caused by power supply net capacity. The experimental results show that the proposed method can be a good measure of the impact of power supply net capacity on electricity sales, the model can also be used to guide the analysis of the trend of electricity sales and provide effective data support for decision making of power companies.
{"title":"Analyzing the effect of power supply net capacity on electricity sales based on growth curve","authors":"Yuze Chen, Jiakui Zhao, Jian Liu, Yuxi Liu, Bingxin Wang, Ouyang Hong, Hongwang Fang, Yaozong Lu","doi":"10.1109/FSKD.2017.8393068","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393068","url":null,"abstract":"Grasping the effect of power supply net capacity on electricity sales has a great significance to analyze the trend of electricity sales accurately. Based on correlation analysis of historical data of the first, second, third industrial and residential electricity sales and power supply net capacity of power company, this paper presents a method of analyzing the effect of power supply net capacity on electricity sales by growth curve. The method eliminates the effect of seasonal factor and random factor of power supply net capacity and electricity sales by X13 seasonal adjustment, calculates the leading time of power supply net capacity ahead of electricity sales by dynamic time warping, calculates load operation ratio of power supply net capacity by growth curve. The method is used for quantitative analysis in studying electricity sales' changes caused by power supply net capacity. The experimental results show that the proposed method can be a good measure of the impact of power supply net capacity on electricity sales, the model can also be used to guide the analysis of the trend of electricity sales and provide effective data support for decision making of power companies.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129346215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393177
Jiqiao Li, Shaohong Zhang, Zongbao Yang
In recent years, with the growing of global computer professional employment demand, the recruitment of computer science is mainly aimed at technology upgrading and technological innovation and so on. Facing the optimistic employment environment, University both at the house and abroad is reforming the computer courses teaching program, increasing the intensity of computer professional skills training. There is no doubt that the professional prospect for computer science is very bright. Under the new employment pressure, it's important to students to strengthen the student's professional knowledge and training of their professional quality. This paper analyzes the professional skills which computer professionals need in the future based on the domestic current employment information and employment situation of the graduates. We make a brief analysis of the professional skills required for computer talent for the future, And put forward some suggestion of reform for a computer specialty course of domestic colleges and universities.
{"title":"Analysis on employment situation of computer industry based on employing information data mining","authors":"Jiqiao Li, Shaohong Zhang, Zongbao Yang","doi":"10.1109/FSKD.2017.8393177","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393177","url":null,"abstract":"In recent years, with the growing of global computer professional employment demand, the recruitment of computer science is mainly aimed at technology upgrading and technological innovation and so on. Facing the optimistic employment environment, University both at the house and abroad is reforming the computer courses teaching program, increasing the intensity of computer professional skills training. There is no doubt that the professional prospect for computer science is very bright. Under the new employment pressure, it's important to students to strengthen the student's professional knowledge and training of their professional quality. This paper analyzes the professional skills which computer professionals need in the future based on the domestic current employment information and employment situation of the graduates. We make a brief analysis of the professional skills required for computer talent for the future, And put forward some suggestion of reform for a computer specialty course of domestic colleges and universities.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132311899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393152
Lian Pan, Jie Su, Hanwu Wang
The relationship between the fairness and benefit tradeoff in regional social resource allocation management is studied and analyzed. Fairness is a basic requirement of different regional entities for social resource competition while benefit maximization by sacrificing fairness is preferred by resource provider. Hence how to balance these two respects and derive the explicit tradeoff point is a key challenging issue. We consider both the fairness requirement constraint and resource benefit maximization and set up an objective optimization formulation. The fairness-benefit tradeoff curve is presented by solving the objective optimization problem, and the derived curve shows the benefits gained with the respect to the extent of fairness sacrifice.
{"title":"Fairness maintenance in social regional resource allocation management","authors":"Lian Pan, Jie Su, Hanwu Wang","doi":"10.1109/FSKD.2017.8393152","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393152","url":null,"abstract":"The relationship between the fairness and benefit tradeoff in regional social resource allocation management is studied and analyzed. Fairness is a basic requirement of different regional entities for social resource competition while benefit maximization by sacrificing fairness is preferred by resource provider. Hence how to balance these two respects and derive the explicit tradeoff point is a key challenging issue. We consider both the fairness requirement constraint and resource benefit maximization and set up an objective optimization formulation. The fairness-benefit tradeoff curve is presented by solving the objective optimization problem, and the derived curve shows the benefits gained with the respect to the extent of fairness sacrifice.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132331707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393114
Yuechun Jiang, Zhongnan He, A. Liu, Zhong-ying Bai
Cascade hydropower station can comprehensively develop hydropower resources of river basin and realize the full use of clean energy, its optimal operation is a dynamic nonlinear multi-objective optimization problem with complex constraints. Biogeography-based optimization (BBO) algorithm is a new evolutionary algorithm based on biogeography. In this paper, dynamic non-uniform mutation operator and mutation strategy of differential evolution algorithm are introduced to improve migration operator and mutation operator of BBO algorithm, which enhance exploration ability of the algorithm and accelerate convergence speed of the algorithm. Improved BBO algorithm is used to solve the multi — objective optimization model of cascade hydropower station, and the optimal solution of the problem is obtained after several times of migration and mutation operation. Taking the optimal operation of a two-stage cascade hydropower station as an example, the feasibility and effectiveness of the proposed model and improved BBO algorithm are verified.
{"title":"Research on optimal operation of cascade hydropower station based on improved biogeography-based optimization algorithm","authors":"Yuechun Jiang, Zhongnan He, A. Liu, Zhong-ying Bai","doi":"10.1109/FSKD.2017.8393114","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393114","url":null,"abstract":"Cascade hydropower station can comprehensively develop hydropower resources of river basin and realize the full use of clean energy, its optimal operation is a dynamic nonlinear multi-objective optimization problem with complex constraints. Biogeography-based optimization (BBO) algorithm is a new evolutionary algorithm based on biogeography. In this paper, dynamic non-uniform mutation operator and mutation strategy of differential evolution algorithm are introduced to improve migration operator and mutation operator of BBO algorithm, which enhance exploration ability of the algorithm and accelerate convergence speed of the algorithm. Improved BBO algorithm is used to solve the multi — objective optimization model of cascade hydropower station, and the optimal solution of the problem is obtained after several times of migration and mutation operation. Taking the optimal operation of a two-stage cascade hydropower station as an example, the feasibility and effectiveness of the proposed model and improved BBO algorithm are verified.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"257 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114057753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393211
L. Shen, Gaobo Yang, Leida Li, Xingming Sun
Exemplar-based image inpainting can be maliciously used for object removal forgery without leaving any perceptual clues. Especially, post-processing might further brings challenges for its blind forensics. In the paper, a robust forensics approach is presented to detect object removal tamper by exemplar-based image inpainting with post-processing, such as JEPG compression, blurring, imnoise, and so on. Object removal changes local texture and gradient smoothness, which destroys the inherent properties of nature images. Two local texture descriptors including LBP (Local Binary Patterns) and GLCM (Gray-level Co-occurrence Matrix) are exploited to measure texture variation, and image gradient is used to describe the structure change. Fourteen statistical features including Zernike zero-order moment, min, max, mean, variance and standard deviation are extracted from them. Then, support vector machine (SVM) is exploited as pattern classifier to determine whether an image has been suffered from object removal or not. Experimental results show the detection robustness for object-removal forgery with post-processing.
{"title":"Robust detection for object removal with post-processing by exemplar-based image inpainting","authors":"L. Shen, Gaobo Yang, Leida Li, Xingming Sun","doi":"10.1109/FSKD.2017.8393211","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393211","url":null,"abstract":"Exemplar-based image inpainting can be maliciously used for object removal forgery without leaving any perceptual clues. Especially, post-processing might further brings challenges for its blind forensics. In the paper, a robust forensics approach is presented to detect object removal tamper by exemplar-based image inpainting with post-processing, such as JEPG compression, blurring, imnoise, and so on. Object removal changes local texture and gradient smoothness, which destroys the inherent properties of nature images. Two local texture descriptors including LBP (Local Binary Patterns) and GLCM (Gray-level Co-occurrence Matrix) are exploited to measure texture variation, and image gradient is used to describe the structure change. Fourteen statistical features including Zernike zero-order moment, min, max, mean, variance and standard deviation are extracted from them. Then, support vector machine (SVM) is exploited as pattern classifier to determine whether an image has been suffered from object removal or not. Experimental results show the detection robustness for object-removal forgery with post-processing.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128467055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393057
Li Tian, Zhen Su
The orthogonal frequency division multiplexing (OFDM) has the advantages of a high spectrum utilization and anti-multipath interference, and can be used in a high-speed data transmission system of the wireless environment. In this paper, an algorithm of channel estimation is deduced based on the channel impulse response (CIR) model of the discrete time in a time-varying channel for the OFDM system. Considering that the normalized doppler shift is very small in the actual mobile communication, so this paper adopts the second-order taylor series expansion to approach the inter-carrier interference (ICI) to simplify the channel estimation model. Moreover, the discrete channel parameters are calculated by maximum likelihood estimation algorithms, and the root mean square error (RMSE) is analyzed by simulations. The improved algorithm can accurately estimate the parameters and improve the efficiency of the algorithm; in addition, the root mean square error and the convergence speed can get better performance.
{"title":"An estimation algorithm of time-varying channels in the OFDM communication system","authors":"Li Tian, Zhen Su","doi":"10.1109/FSKD.2017.8393057","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393057","url":null,"abstract":"The orthogonal frequency division multiplexing (OFDM) has the advantages of a high spectrum utilization and anti-multipath interference, and can be used in a high-speed data transmission system of the wireless environment. In this paper, an algorithm of channel estimation is deduced based on the channel impulse response (CIR) model of the discrete time in a time-varying channel for the OFDM system. Considering that the normalized doppler shift is very small in the actual mobile communication, so this paper adopts the second-order taylor series expansion to approach the inter-carrier interference (ICI) to simplify the channel estimation model. Moreover, the discrete channel parameters are calculated by maximum likelihood estimation algorithms, and the root mean square error (RMSE) is analyzed by simulations. The improved algorithm can accurately estimate the parameters and improve the efficiency of the algorithm; in addition, the root mean square error and the convergence speed can get better performance.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114273883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393403
Bin Mu, Site Li, Shijin Yuan
Under the circumstance of environment deterioration in cities, people are increasingly concerned about urban environment quality, especially air quality. As a result, it is of great value to provide accurate forecast of air quality index and show the statistics on the smart city platform. In order to forecast urban AQI values the next day, MATLAB is applied to deal with AQI correlative data stored in MySQL database. To be specific, principal component analysis of AQI influencing factors is firstly made, including aspects of weather, industrial waste gas and individual air quality indexes at the present day. Then, to have a better fitting performance than other traditional methods, circular multi-population genetic algorithm (CMPGA) is adopted to optimize initial weights and thresholds of prediction neural network. Afterwards, the improved network is trained to provide AQI forecast the next day. The whole prediction model is named PCA-CMFGA-BP and the core of the model is PCA and CMPGA. To verify accuracy of the model's forecast results, the study uses four statistical indexes to evaluate AQI forecast results (RMSE, MSE, MAPE and MAD) and compares the model with GABP, partial least square regression, principal component estimate regression and support vector regression to prove the model's superiority. To conclude, prediction fitting error is reduced by optimizing parameters of circular multi-population algorithm and choosing the most suitable training function for prediction network. The performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in urban AQI forecast on the smart city platform in the future.
{"title":"An improved effective approach for urban air quality forecast","authors":"Bin Mu, Site Li, Shijin Yuan","doi":"10.1109/FSKD.2017.8393403","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393403","url":null,"abstract":"Under the circumstance of environment deterioration in cities, people are increasingly concerned about urban environment quality, especially air quality. As a result, it is of great value to provide accurate forecast of air quality index and show the statistics on the smart city platform. In order to forecast urban AQI values the next day, MATLAB is applied to deal with AQI correlative data stored in MySQL database. To be specific, principal component analysis of AQI influencing factors is firstly made, including aspects of weather, industrial waste gas and individual air quality indexes at the present day. Then, to have a better fitting performance than other traditional methods, circular multi-population genetic algorithm (CMPGA) is adopted to optimize initial weights and thresholds of prediction neural network. Afterwards, the improved network is trained to provide AQI forecast the next day. The whole prediction model is named PCA-CMFGA-BP and the core of the model is PCA and CMPGA. To verify accuracy of the model's forecast results, the study uses four statistical indexes to evaluate AQI forecast results (RMSE, MSE, MAPE and MAD) and compares the model with GABP, partial least square regression, principal component estimate regression and support vector regression to prove the model's superiority. To conclude, prediction fitting error is reduced by optimizing parameters of circular multi-population algorithm and choosing the most suitable training function for prediction network. The performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in urban AQI forecast on the smart city platform in the future.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124084697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In P2P (Peer-to-Peer) video streaming systems using unstructured mesh, data scheduling is an important factor on system performance. An optimal data scheduling scheme should achieve two objectives ideally. The first objective is to optimize the perceived video quality of peers. The second objective is to maximize the network throughput, i.e., utilize the upload bandwidth of peers maximally. However, the optimized perceived video quality may not bring a maximized network throughput, and vice versa. In the paper, to better achieve the two objectives simultaneously, we formulate the data scheduling problem as a multi-objective optimization problem. To solve the multi-objective optimization problem, we propose a multi-objective particle swarm optimization data scheduling algorithm by encoding the peers' neighbors as the locations of the particles. Through simulations, we demonstrate the proposed algorithm outperforms other algorithms in terms of the perceived video quality and the utilization of peers' upload capacity.
{"title":"A multi-objective particle swarm optimization data scheduling algorithm for peer-to-peer video streaming","authors":"Pingshan Liu, Xiaoyi Xiong, Guimin Huang, Yimin Wen","doi":"10.1109/FSKD.2017.8393220","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393220","url":null,"abstract":"In P2P (Peer-to-Peer) video streaming systems using unstructured mesh, data scheduling is an important factor on system performance. An optimal data scheduling scheme should achieve two objectives ideally. The first objective is to optimize the perceived video quality of peers. The second objective is to maximize the network throughput, i.e., utilize the upload bandwidth of peers maximally. However, the optimized perceived video quality may not bring a maximized network throughput, and vice versa. In the paper, to better achieve the two objectives simultaneously, we formulate the data scheduling problem as a multi-objective optimization problem. To solve the multi-objective optimization problem, we propose a multi-objective particle swarm optimization data scheduling algorithm by encoding the peers' neighbors as the locations of the particles. Through simulations, we demonstrate the proposed algorithm outperforms other algorithms in terms of the perceived video quality and the utilization of peers' upload capacity.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131268687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8392914
Alex Bertei, Luciana Foss, S. Cavalheiro, R. Reiser
Graph Grammars are a visual formal language for which there are several techniques of system specification and verification. This fact makes them an attractive option for describing complex systems. Fuzzy graph grammars generalize the concept of graph grammars, using fuzzy graphs. A fuzzy graph is composed of vertices and edges that have an associated membership value, which varies within a range of 0 to 1. Due to the lack of technique and analysis tools for fuzzy graph grammars, their use is still quite limited. One way to allow the analysis of fuzzy graphs grammars is using the extension of existing graph grammar approaches, including the concept of membership in the graph components. There is a relational approach of graph grammars that allows the use of theorem provers to perform property analysis of systems described in this language. This approach is the basis of a translation of graph grammars into the Event-B language, which enables the use of theorem provers of the Rodin tool. Therefore, the aim of this work is to extend this graph grammar approach, including fuzzy concepts, to allow the use of the theorem proving technique to analyze fuzzy graph grammars. In order to set this extension was first necessary to define the notion of typed fuzzy graph grammars.
{"title":"A relational approach of fuzzy graph grammars","authors":"Alex Bertei, Luciana Foss, S. Cavalheiro, R. Reiser","doi":"10.1109/FSKD.2017.8392914","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8392914","url":null,"abstract":"Graph Grammars are a visual formal language for which there are several techniques of system specification and verification. This fact makes them an attractive option for describing complex systems. Fuzzy graph grammars generalize the concept of graph grammars, using fuzzy graphs. A fuzzy graph is composed of vertices and edges that have an associated membership value, which varies within a range of 0 to 1. Due to the lack of technique and analysis tools for fuzzy graph grammars, their use is still quite limited. One way to allow the analysis of fuzzy graphs grammars is using the extension of existing graph grammar approaches, including the concept of membership in the graph components. There is a relational approach of graph grammars that allows the use of theorem provers to perform property analysis of systems described in this language. This approach is the basis of a translation of graph grammars into the Event-B language, which enables the use of theorem provers of the Rodin tool. Therefore, the aim of this work is to extend this graph grammar approach, including fuzzy concepts, to allow the use of the theorem proving technique to analyze fuzzy graph grammars. In order to set this extension was first necessary to define the notion of typed fuzzy graph grammars.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117239161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-29DOI: 10.1109/FSKD.2017.8393146
Chun-man Yan, Genyuan Lu, Yingyi Liu, Xiang-yu Deng
Because of the convergence speed and the simple computation, the Particle Swarm Optimization (PSO) has been developing quickly, and many variants of the PSO have been proposed. By using some strategies, the major aim for improving the PSO is to obtain the global search ability at the early search stage and the better local search performance at the later stage. This paper proposed a modified PSO with exponential decay weight. By introducing a constraint factor to the velocity updating equation of the original PSO, and adopting the exponential decay mode for the inertia weight, a well global search ability at the early stage of the optimization procedure and a high local search performance at the later period can be obtained. We evaluate our algorithm with four benchmark functions and analyze the contributions of the exponential decay mode. For three common measures indices: convergence speed, convergence stability, and optimization success times, the experimental results show that the modified algorithm outperforms favorably against the famous improved PSO such as linear weight PSO and the constraint factor PSO.
{"title":"A modified PSO algorithm with exponential decay weight","authors":"Chun-man Yan, Genyuan Lu, Yingyi Liu, Xiang-yu Deng","doi":"10.1109/FSKD.2017.8393146","DOIUrl":"https://doi.org/10.1109/FSKD.2017.8393146","url":null,"abstract":"Because of the convergence speed and the simple computation, the Particle Swarm Optimization (PSO) has been developing quickly, and many variants of the PSO have been proposed. By using some strategies, the major aim for improving the PSO is to obtain the global search ability at the early search stage and the better local search performance at the later stage. This paper proposed a modified PSO with exponential decay weight. By introducing a constraint factor to the velocity updating equation of the original PSO, and adopting the exponential decay mode for the inertia weight, a well global search ability at the early stage of the optimization procedure and a high local search performance at the later period can be obtained. We evaluate our algorithm with four benchmark functions and analyze the contributions of the exponential decay mode. For three common measures indices: convergence speed, convergence stability, and optimization success times, the experimental results show that the modified algorithm outperforms favorably against the famous improved PSO such as linear weight PSO and the constraint factor PSO.","PeriodicalId":236093,"journal":{"name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132996509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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