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2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)最新文献

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Palmprint verification based on textural features by using Gabor filters based GLCM and wavelet 基于Gabor滤波的GLCM和小波纹理特征掌纹验证
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-07 DOI: 10.1109/CSIEC.2017.7940164
Farzam Kharaji Nezhadian, S. Rashidi
{"title":"Palmprint verification based on textural features by using Gabor filters based GLCM and wavelet","authors":"Farzam Kharaji Nezhadian, S. Rashidi","doi":"10.1109/CSIEC.2017.7940164","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940164","url":null,"abstract":"The palmprint is one of the most reliable physiological characteristics Among different approaches that exist in biometric. palmprint due to having high acceptability, stability and low cost of implementation has drawn attention from researchers. In this paper, we considered the palmprint as a texture and applied two types of feature extraction methods, namely Gabor filters based Gray-Level Co-occurrence Matrix and Discrete Wavelet Transform. In total 350 features that are extracted by these approaches, fifty superior features selected by the forward feature selection algorithm. Features are classified with new method of using reference features in order to achieve higher resolution and by using K-Nearest Neighbor and Fuzzy K-Nearest Neighbor classifiers. In CASIA testing database of 5,502 palmprint samples from 312 palms, we achieved Equal Error Rate of 1.25% ± 0.56 and Accuracy of 98.75% ±0.56 with 60% train by K-Nearest Neighbor classifier.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128539440","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}
引用次数: 6
Optimal locating and sizing of DG and D-STATCOM using Modified Shuffled Frog Leaping Algorithm 基于改进的青蛙跳跃算法优化DG和D-STATCOM的定位和尺寸
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-07 DOI: 10.1109/CSIEC.2017.7940157
M. Moazzami, G. Gharehpetian, Hossein Shahinzadeh, S. Hosseinian
{"title":"Optimal locating and sizing of DG and D-STATCOM using Modified Shuffled Frog Leaping Algorithm","authors":"M. Moazzami, G. Gharehpetian, Hossein Shahinzadeh, S. Hosseinian","doi":"10.1109/CSIEC.2017.7940157","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940157","url":null,"abstract":"In recent years, by restructuring the power systems, the power plant companies are going to improve the quality of the power and the reliability of the distribution systems by using the modern instruments. Also, using the distributed generation sources (DGs) and distribution statistic synchronized compensator (D-STATCOM) in distribution systems has been increased. The installation location and the capacity of these instruments are some of the main factors of impression of such instruments in affecting the improvement of the power quality indices such as the voltage stability and the reduction of the distribution systems losses. In this article, in order to determine the optimal installation position of these instruments, an objective function consisted of equipment's installation and the system energy losses costs is composed. Furthermore, the Modified Shuffled Frog Leaping Algorithm (MSFLA) is applied to minimize the objective function to achieve the optimal place and size of these instruments in distribution system. The proposed method optimization result is compared with the results derived from the genetic algorithm. IEEE 33 Buses standard distribution systems is used as the test case. Simulation results show the effectiveness of the proposed approach.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"33 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129740400","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}
引用次数: 26
Using Recurrence quantification analysis and Generalized Hurst Exponents of ECG for human authentication 将递归量化分析和广义赫斯特指数应用于心电识别
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-07 DOI: 10.1109/CSIEC.2017.7940172
Fatemeh Parastesh Karegar, A. Fallah, S. Rashidi
{"title":"Using Recurrence quantification analysis and Generalized Hurst Exponents of ECG for human authentication","authors":"Fatemeh Parastesh Karegar, A. Fallah, S. Rashidi","doi":"10.1109/CSIEC.2017.7940172","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940172","url":null,"abstract":"Previous works show that the electrocardiogram is a promising signal to be used as a biometric trait. The nonlinear methods for computing the dynamical properties of ECG signal, have been previously used. Since each of the large scale features of recurrence plots of ECG is related quite simply to time-domain features, they can provide good result in biometric system. In this paper we apply Rescaled Range Analysis (RSA), Higuchi's Fractal Dimension (HFD), Detrended Fluctuation Analysis (DFA), Generalized Hurst Exponent (GHE) and Recurrence quantification analysis (RQA) to extract features for authentication system. Support Vector Machine is used to classify the nonlinear features. The proposed approach has been tested using 18 different subjects ECG signal of MIT-BIH Normal Sinus Rhythm Database. The obtained results show that the authentication accuracy is 96.07±0.86%.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126103551","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}
引用次数: 8
EEG-based multi-class motor imagery classification using variable sized filter bank and enhanced One Versus One classifier 基于脑电图的多类运动图像分类，采用可变大小滤波器组和增强的一对一分类器
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-07 DOI: 10.1109/CSIEC.2017.7940174
Mohammadreza Edalati Sharbaf, A. Fallah, S. Rashidi
{"title":"EEG-based multi-class motor imagery classification using variable sized filter bank and enhanced One Versus One classifier","authors":"Mohammadreza Edalati Sharbaf, A. Fallah, S. Rashidi","doi":"10.1109/CSIEC.2017.7940174","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940174","url":null,"abstract":"Motor imagery BCI is a system that is very useful to help people with disabilities who can't move their limbs. These systems use brain activity patterns that are made from motor imagery without actual movement. In this paper, we proposed enhanced OVO structure to classify EEG-based multi-class motor imagery signals. Also, variable sized filter bank is proposed to overcome the weakness of fixed sized filter bank that is used several times. SFFS channel selection is one of the efficient methods which is used to obtain the best channels. The results of four-class classification of BCI competition dataset 2a, show that the performance is improved to 0.63 kappa score.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"70 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113992901","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}
引用次数: 8
Optimal design of fractional order fuzzy PID controller with simultaneous auto-tuned fuzzy control rules and membership functions 同时自整定模糊控制规则和隶属函数的分数阶模糊PID控制器的优化设计
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940179
H. N. Chaleshtori, S. Mohammadi, E. Bijami
{"title":"Optimal design of fractional order fuzzy PID controller with simultaneous auto-tuned fuzzy control rules and membership functions","authors":"H. N. Chaleshtori, S. Mohammadi, E. Bijami","doi":"10.1109/CSIEC.2017.7940179","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940179","url":null,"abstract":"This paper proposes a new intelligent particle swarm optimization (PSO) based method for design of optimal fractional order fuzzy PID (FOFPID) controller with simultaneous auto-tuned fuzzy control rules and membership functions. In the proposed method the parameters of FOFPID controller including input scaling factors, output scaling factors, fractional order of derivative and integrator, fuzzy rule base and membership functions are considered as tuning parameters and optimized simultaneously using PSO algorithm. Moreover, to reduce the fuzzy system design effort and computational complexity, a novel simultaneous tuning approach is proposed for determining the membership functions and fuzzy rule base. The newly suggested design approach provides a flexible controller with simple structure and straightforward algorithm. To evaluate the effectiveness of the proposed method, the proposed FOFPID controller is applied to solve the Load Frequency Control (LFC) problem in a representative power system with considerations governor saturation and the results are compared to the one obtained by a FOFPID controller with fixed fuzzy part and a fractional order PID (FOPID) controller. Simulation results indicate the superiority of proposed method.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122524562","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}
引用次数: 3
Verification based on palm vein by estimating wavelet coefficient with autoregressive model 基于自回归模型估计小波系数的掌纹验证
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940166
Fereshte Yazdani, M. E. Andani
{"title":"Verification based on palm vein by estimating wavelet coefficient with autoregressive model","authors":"Fereshte Yazdani, M. E. Andani","doi":"10.1109/CSIEC.2017.7940166","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940166","url":null,"abstract":"Biometric is a pattern recognition system that automatically identifies people according to their physiologic and behavioral properties. Among the physiologic properties, hand has a special place so that all features of hand like palm lines, inner knuckles, external knuckles and geometry could be used. More recently, the usage of blood vessels pattern in the palm, in addition to the high acceptability, is considered by researchers due to the higher uniqueness and durability in comparison to the palm. In this article, the new method based on the estimate of wavelet coefficient with autoregressive model is used to extract the texture feature for verification. The features from the 600 palm images captured from 50 individuals are classified by the new methods of support vector machine and K-nearest neighbor classifier and eventually results in evaluation with equal error rate and Accuracy standards.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117074293","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}
引用次数: 4
An effective method of multi-label feature selection employing evolutionary algorithms 一种利用进化算法进行多标签特征选择的有效方法
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940162
Shima Kashef, H. Nezamabadi-pour
{"title":"An effective method of multi-label feature selection employing evolutionary algorithms","authors":"Shima Kashef, H. Nezamabadi-pour","doi":"10.1109/CSIEC.2017.7940162","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940162","url":null,"abstract":"In multi-label data, each instance belongs to a set of labels, instead of one label. Due to the increasing number of modern applications for multi-label data, multi-label classification has attracted the attention of many researchers. Similar to single label data, eliminating irrelevant and/or redundant features plays an important role in improving the classifier performance. In this paper, meta-heuristic algorithms are employed to solve multi-label feature selection problem. Since the number of features in multi-label datasets is usually high, using these algorithms is not affordable in terms of computational complexity, and they may fail to find optimal feature subset. To solve this problem, irrelevant features are first removed using a filter method. Then, evolutionary algorithms are employed to find the most salient features. Experimental results demonstrate the efficiency of our proposed method compared to some existing multi-label features selection methods.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115474446","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}
引用次数: 8
Optimization of multi-wavelength Brillouin-Raman fiber laser in NALM design by employment genetic algorithm 利用遗传算法优化NALM设计中多波长布里渊-拉曼光纤激光器
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940178
G. Mamdoohi, S. Saryazdi
{"title":"Optimization of multi-wavelength Brillouin-Raman fiber laser in NALM design by employment genetic algorithm","authors":"G. Mamdoohi, S. Saryazdi","doi":"10.1109/CSIEC.2017.7940178","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940178","url":null,"abstract":"This paper aims to optimize multi-wavelength Brillouin-Raman fiber laser (MBRFL) utilizing nonlinear amplifying loop mirror (NALM) design through employment a simple genetic algorithm. This is carried out in order to evaluate large degree of freedom of parameters through transmitted power as a fitness function that can be exploited to optimize the behavior of the NALM without repeating experiment. The genetic algorithm is intelligent enough that can support different parameters to achieve maximum transmitted power of 35 mW. This is attained when the optimized parameters including 5 km of dispersing compensating fiber length with Raman pump power of 600 mW and attenuator value of −30 dB are incorporated.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124293568","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}
引用次数: 3
Optimization of plasmonic color filters for CMOS image sensors by genetic algorithm 基于遗传算法的CMOS图像传感器等离子体彩色滤光片优化
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940161
F. F. Mahani, A. Mahanipour, A. Mokhtari
{"title":"Optimization of plasmonic color filters for CMOS image sensors by genetic algorithm","authors":"F. F. Mahani, A. Mahanipour, A. Mokhtari","doi":"10.1109/CSIEC.2017.7940161","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940161","url":null,"abstract":"Utilization of a plasmonic nanohole array as a color filter, proposes important advantages like the compatibility with CMOS processes. A color filter is an important component for applications, such as LCDs, LEDs, CMOS image sensors, etc. In this article, a set of primary color filters (red, green and blue) are designed by an optimization procedure, employing genetic algorithm integrated with Lumerical FDTD software. The filters consist of a square lattice of nanoholes in an aluminum film on a silicon dioxide substrate. They are suitable for using in CMOS image sensors. Despite the practical restrictions to simplify the fabrication, the optical response of the filters have shown a transmission peak of 30–43 percent with a FWHM of 40 (nm), 50 (nm) and 80 (nm) in accurate resonant wavelengths of red, green, and blue filters, respectively. These results demonstrate the efficacy of the proposed optimization method.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121186233","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}
引用次数: 13
MVP: Memetic Voter Patterns for aspect extraction in sentiment analysis 情感分析中面向方面提取的模因选民模式
2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC) Pub Date : 2017-03-01 DOI: 10.1109/CSIEC.2017.7940154
Hamidreza Keshavarz, M. S. Abadeh
{"title":"MVP: Memetic Voter Patterns for aspect extraction in sentiment analysis","authors":"Hamidreza Keshavarz, M. S. Abadeh","doi":"10.1109/CSIEC.2017.7940154","DOIUrl":"https://doi.org/10.1109/CSIEC.2017.7940154","url":null,"abstract":"The reviews in online resources are used extensively to evaluate the quality of various subjects, such as products. The products have several aspects, and extracting these aspects from review texts is a sub-task of aspect-based sentiment analysis. This paper proposes a novel algorithm, named Memetic Voter Patterns, or MVP, to identify aspect words, by using patterns of parts-of-speeches of their adjacent words. This method yields a higher accuracy than previous methods and gives a better understanding of the structure of sentences around an aspect. This method is based on a voting system. The patterns of the part-of-speeches around aspects are identified by incorporating a memetic algorithm. This method can have applications in other subfields of opinion mining, such as finding sentiment phrases.","PeriodicalId":166046,"journal":{"name":"2017 2nd Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131821083","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}
引用次数: 1
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