2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)最新文献

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Fuzzy controller tuning of a mobile robot for exploration and safe navigation in constrained environment 约束环境下移动机器人探索与安全导航的模糊控制器整定
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865783
E. Vans, G. Vachkov
{"title":"Fuzzy controller tuning of a mobile robot for exploration and safe navigation in constrained environment","authors":"E. Vans, G. Vachkov","doi":"10.1109/CYBERNETICSCOM.2013.6865783","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865783","url":null,"abstract":"In this paper we present a novel fuzzy controller structure for a mobile robot with the purpose for exploration of a constrained environment with obstacles. The proposed fuzzy rule base contains redundancy in some of the fuzzy rules, i.e., several consequents could be used. At each step we make random selection of one of these consequents. This is called in our paper Random Selection Fuzzy Rule Base. The simulation results show that the proposed fuzzy rule base makes the robot more agile compared with the results based on the fixed fuzzy rule base. Further on we applied a modified version of the particle swarm optimization in order to tune the fuzzy controller parameters. The simulations show that the optimized fuzzy controller allows the robot to navigate more safely, avoiding obstacles and to travel longer trajectories. Thus, the robot with the tuned fuzzy controller is able to explore wider area of the environment than the robot with the untuned controller.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115593444","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
Javanese speech levels machine translation: Improved parallel text alignment based on impossible pair limitation 爪哇语语音级别机器翻译:基于不可能对限制的改进并行文本对齐
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865773
A. Wibawa, A. Nafalski, Wayah Firdaus Mahmudy
{"title":"Javanese speech levels machine translation: Improved parallel text alignment based on impossible pair limitation","authors":"A. Wibawa, A. Nafalski, Wayah Firdaus Mahmudy","doi":"10.1109/CYBERNETICSCOM.2013.6865773","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865773","url":null,"abstract":"A machine translation is developed to preserve the existence of Javanese speech levels. The machine translation relies on a phrase-based bi-text alignment to form the language corpora. The edit shifting distance is applied to increase the alignment efficiency. However, improper alignment contributed by recorded impossible pair and insufficient data training is still detected. This paper proposes a new improvement of the developed alignment algorithm based on the impossible pair restriction. The paper compares three situations: the fundamental approach (AL1) the basic algorithm with extended data training (AL2) and improved algorithm with standard data training (AL3). Based on experimental results, AL3 (A=90.5%)is remarkably accurate than AL1 (A=79.6%) and AL2 (A=85.9).","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122765732","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
Performance evaluation of swarm intelligence on model-based PID tuning 群智能在基于模型的PID整定中的性能评价
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865778
D. A. R. Wati
{"title":"Performance evaluation of swarm intelligence on model-based PID tuning","authors":"D. A. R. Wati","doi":"10.1109/CYBERNETICSCOM.2013.6865778","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865778","url":null,"abstract":"PID controller has been implemented in many applications due to its simplicity and its good performance. The main problem in PID controller design is tuning its parameters. In order to result in optimal performance, PID parameters should be tuned precisely. An alternative approach that can be used in PID parameters tuning is using swarm intelligence including Particle Swarm Optimization (PSO) and Artificial Bee Colony Optimization (ABCO). This paper presents the performance evaluation of both techniques on PID controller tuning. The tuning is done offline based on a model of plant. The objective function is minimizing the mean square error of step response. Both techniques result in the same optimal solution and produce better response characteristics compared to conventional PID tuning by Ziegler-Nichols method and manual tuning.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121394609","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
Experiments on Indonesian-Japanese statistical machine translation 印尼语-日语统计机器翻译实验
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865786
H. Simon, A. Purwarianti
{"title":"Experiments on Indonesian-Japanese statistical machine translation","authors":"H. Simon, A. Purwarianti","doi":"10.1109/CYBERNETICSCOM.2013.6865786","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865786","url":null,"abstract":"Based on the characteristics of Indonesian and Japanese language, we did several experiments on the additional process to an Indonesian-Japanese statistical machine translation (SMT). We proposed several additional processes such as employing the POS tag information, adding the size of monolingual target corpus, using Indonesian stemmer in Indonesian to Japanese translation, eliminating Japanese particle in Japanese to Indonesian translation, and the elimination of NE tag. The experimental result showed that compared to the baseline of adding no process to the default SMT engine (here, we use Moses), the highest BLEU score was achieved by the elimination of Japanese particle in Japanese to Indonesian translation.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134257746","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: 10
Hybrid genetic algorithms for multi-period part type selection and machine loading problems in flexible manufacturing system 柔性制造系统多周期零件选型和机器加载问题的混合遗传算法
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865795
W. Mahmudy, Romeo M. Mariana, L. Luong
{"title":"Hybrid genetic algorithms for multi-period part type selection and machine loading problems in flexible manufacturing system","authors":"W. Mahmudy, Romeo M. Mariana, L. Luong","doi":"10.1109/CYBERNETICSCOM.2013.6865795","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865795","url":null,"abstract":"This paper addresses the multi-period part type selection and machine loading problems in flexible manufacturing system (FMS) with the objective of maximizing system throughput and maintaining balance of the system for the whole planning horizon. Various flexibilities including machine and tool flexibility, routing flexibility, and alternative production plans are considered. Hybridization of real coded genetic algorithms (RCGA) and variable neighborhood search (VNS) is proposed to simultaneously solve these NP-hard problems for the whole periods. The proposed hybrid genetic algorithms (HGA) are designed to balance the power of the algorithms to explore a huge search space and to exploit local search areas. The experiments show that addressing the problems for the whole periods simultaneously will produce better results comparable to those achieved by the sequential approach.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115570203","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: 27
Web crawler utilization for resource search on Indonesian anti-plagiarism detection: Pemanfaatan web crawler untuk pencarian referensi pada deteksi anti-plagiarisme dokumen Bahasa Indonesia
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865793
A. Wibowo, A. Arifianto, Adeva Oktoveri, Arif M Barmawi
{"title":"Web crawler utilization for resource search on Indonesian anti-plagiarism detection: Pemanfaatan web crawler untuk pencarian referensi pada deteksi anti-plagiarisme dokumen Bahasa Indonesia","authors":"A. Wibowo, A. Arifianto, Adeva Oktoveri, Arif M Barmawi","doi":"10.1109/CYBERNETICSCOM.2013.6865793","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865793","url":null,"abstract":"Matching one document with other documents is one of anti-plagiarism tasks. Matching can be performed both intra and extra-corpal. This paper will discuss extra-corpal matching utilize the web crawlers as reference search. The role of web-crawler described in extra-corpal anti-plagiarism architecture. Matching of plagiarism indication will use Modified Histogram Intersection based on N-Gram of term. Similarity value utilizing modified normalized histogram intersection that devoted to matching extra corpal. Based on our experiment the best accuracy is given in 0.4 and 0.5 threshold value that give 94% accuracy.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125472714","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: 0
Performance of a hierarchical temporal memory network in noisy sequence learning 一种分层时间记忆网络在噪声序列学习中的性能
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865779
Daniel E. Padilla, R. Brinkworth, M. McDonnell
{"title":"Performance of a hierarchical temporal memory network in noisy sequence learning","authors":"Daniel E. Padilla, R. Brinkworth, M. McDonnell","doi":"10.1109/CYBERNETICSCOM.2013.6865779","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865779","url":null,"abstract":"As neurobiological evidence points to the neocortex as the brain region mainly involved in high-level cognitive functions, an innovative model of neocortical information processing has been recently proposed. Based on a simplified model of a neocortical neuron, and inspired by experimental evidence of neocortical organisation, the Hierarchical Temporal Memory (HTM) model attempts at understanding intelligence, but also at building learning machines. This paper focuses on analysing HTM's ability for online, adaptive learning of sequences. In particular, we seek to determine whether the approach is robust to noise in its inputs, and to compare and contrast its performance and attributes to an alternative Hidden Markov Model (HMM) approach. We reproduce a version of a HTM network and apply it to a visual pattern recognition task under various learning conditions. Our first set of experiments explore the HTM network's capability to learn repetitive patterns and sequences of patterns within random data streams. Further experimentation involves assessing the network's learning performance in terms of inference and prediction under different noise conditions. HTM results are compared with those of a HMM trained at the same tasks. Online learning performance results demonstrate the HTM's capacity to make use of context in order to generate stronger predictions, whereas results on robustness to noise reveal an ability to deal with noisy environments. Our comparisons also, however, emphasise a manner in which HTM differs significantly from HMM, which is that HTM generates predicted observations rather than hidden states, and each observation is a sparse distributed representation.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121791031","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: 18
Application and comparison of neural networks and optimization algorithms as a virtual angle of attack sensor 神经网络与优化算法在虚拟攻角传感器中的应用与比较
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865771
K. Kufieta, Kamsan Sivamoorthy, P. Vorsmann
{"title":"Application and comparison of neural networks and optimization algorithms as a virtual angle of attack sensor","authors":"K. Kufieta, Kamsan Sivamoorthy, P. Vorsmann","doi":"10.1109/CYBERNETICSCOM.2013.6865771","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865771","url":null,"abstract":"Angle of attack (AOA) measurement is an important part in flight control. AOA sensor failures caused several major accidents in aviation history (e.g. Flight 888T or Air France flight 447). In most cases one or two of three sensors fail due to e.g. ice freezing over and the flight computer chooses the faulty signal. A fourth sensor that works with a completely different principle could be compared to the remaining sensors and even used as replacement in case of total sensor loss. The presented method estimates an AOA to fit the data from thrust lever position, elevator position, airspeed sensor and acceleration sensors. For this purpose neural networks and optimization algorithms are compared with each other. The great advantage of this method is that it is applicable to nearly every flight computer and needs no prior knowledge of the airplane. Thus it could improve the security of flight control significantly.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131125850","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
A distance-based feature-encoding technique for protein sequence classification in bioinformatics 生物信息学中基于距离的蛋白质序列分类特征编码技术
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865770
M. Iqbal, I. Faye, A. Said, B. Samir
{"title":"A distance-based feature-encoding technique for protein sequence classification in bioinformatics","authors":"M. Iqbal, I. Faye, A. Said, B. Samir","doi":"10.1109/CYBERNETICSCOM.2013.6865770","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865770","url":null,"abstract":"Bioinformatics has been emerging as a new research dimension since the last century by combining computer science and biology techniques for the automatic analysis of biological sequence data. The volume of the biological data gathered under different sequencing projects is increasing exponentially. These sequences contain extremely important information about genes, their structure and function. Computational techniques which involve machine learning and pattern recognition are becoming very useful on Bioinformatics data like DNA and protein. Protein classification into different groups could be used for knowing the structure or the function of unknown protein sequence. The process of classifying protein amino acid sequences into a family /superfamily is a very complex problem. However, from among other major issues in a protein classification, the critical one is an accurate representation of amino acid sequence during the feature extraction. In this work, we have proposed a distance-based feature-encoding method; the proposed technique has been tested with different classifiers, which have shown better results than the previously available techniques for superfamily classification of protein sequences. The maximum average classification accuracy obtained was 91.2%. The dataset used in the experiments was taken from the well known UniProtKB protein database.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"223 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120899796","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: 7
Low cost vision-based real-time lane recognition and lateral pose estimation 基于低成本视觉的实时车道识别和横向姿态估计
2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM) Pub Date : 2013-12-01 DOI: 10.1109/CYBERNETICSCOM.2013.6865800
Sofyan Tan, Agnes, J. Mae
{"title":"Low cost vision-based real-time lane recognition and lateral pose estimation","authors":"Sofyan Tan, Agnes, J. Mae","doi":"10.1109/CYBERNETICSCOM.2013.6865800","DOIUrl":"https://doi.org/10.1109/CYBERNETICSCOM.2013.6865800","url":null,"abstract":"Real-time road lane recognition and position estimation algorithm in small vehicle is generally limited by the amount of processing power available. The goal of this research is to develop a light-weight algorithm to recognize a pair of road lane markers using computer vision and to estimate the vehicle position relative to the lane markers. The road lane recognition algorithm uses inverse perspective mapping of detected lines to speed-up recognition of the lane markers pair, and then a color matching stage is employed to reduce false recognition. The algorithm is implemented in a small battery-powered processing unit and evaluated in a miniature four-wheel vehicle to recognize a pair of lane markers on the floor and to estimate the vehicle's pose on the floor relative to the lane markers. The algorithm managed to estimate the lateral position and the orientation of the vehicle with accuracy about 1.5 cm and 2 degree respectively, and an estimation rate of 2.7 Hz.","PeriodicalId":351051,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133485967","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: 2
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