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RETRACTED ARTICLE: Horizontal global solar radiation estimation using hybrid SVM-firefly and SVM-wavelet algorithms: a case study

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Natural Hazards 2015年第3期102卷 1613-1614页

作者： Mohammadi, Kasra Shamshirband, Shahaboddin Danesh, Amir Seyed Zamani, Mazdak Sudheer, Ch. Department of Mechanical and Industrial Engineering University of Massachusetts Amherst USA Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Computer Science Kean University Union USA Department of Civil and Environmental Engineering ITM University Gurugaon India

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Behavior selection system based on emotional variations

Behavior selection system based on emotional variations

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Wisanu Jitviriya Masato Koike Eiji Hayashi Graduated School of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan Dept. of Mechanical Information Science and Technology Kyushu Institute of Technology Fukuoka Japan

Designing robots with cognition and consciousness resembling that of human or animal has become an important application of intelligent autonomous robot, in order to achieve a more effective human-robot interaction. On the grounds of dynamic system, the primary structure of a behavioral-emotional model of the robots consists of three processes: recognition process, cognition process and behavioral-emotional expression process. Therefore, in this paper, we propose a behavioral-emotional selection model for a conscious behavior robot (Conbe-I) based on the Self-Organizing Map (SOM) learning and the discrete stochastic state-space mathematical model (Markov model) that mainly consider the issues of an autonomous action selection corresponds to the emotional state transition and the emotional expression of an autonomous robot. Finally, the experimental results show the efficiency of the proposed system.

关键词： Mathematical model Markov processes Cognition Robot sensing systems Service robots Image recognition

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RETRACTED ARTICLE: Temperature-based estimation of global solar radiation using soft computing methodologies

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Theoretical and Applied Climatology 2015年第1期125卷 101-112页

作者： Mohammadi, Kasra Shamshirband, Shahaboddin Danesh, Amir Seyed Abdullah, Mohd Shahidan Zamani, Mazdak Faculty of Mechanical Engineering University of Kashan Kashan Iran Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Advanced Informatics School Universiti Teknologi Malaysia Kuala Lumpur Malaysia

Precise knowledge of solar radiation is indeed essential in different technological and scientific applications of solar energy. Temperature-based estimation of global solar radiation would be appealing owing to broad availability of measured air temperatures. In this study, the potentials of soft computing techniques are evaluated to estimate daily horizontal global solar radiation (DHGSR) from measured maximum, minimum, and average air temperatures (T max, T min, and T avg) in an Iranian city. For this purpose, a comparative evaluation between three methodologies of adaptive neuro-fuzzy inference system (ANFIS), radial basis function support vector regression (SVR-rbf), and polynomial basis function support vector regression (SVR-poly) is performed. Five combinations of T max, T min, and T avg are served as inputs to develop ANFIS, SVR-rbf, and SVR-poly models. The attained results show that all ANFIS, SVR-rbf, and SVR-poly models provide favorable accuracy. Based upon all techniques, the higher accuracies are achieved by models (5) using T max–T min and T max as inputs. According to the statistical results, SVR-rbf outperforms SVR-poly and ANFIS. For SVR-rbf (5), the mean absolute bias error, root mean square error, and correlation coefficient are 1.1931 MJ/m2, 2.0716 MJ/m2, and 0.9380, respectively. The survey results approve that SVR-rbf can be used efficiently to estimate DHGSR from air temperatures.

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RETRACTED ARTICLE: Day of the year-based prediction of horizontal global solar radiation by a neural network auto-regressive model

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Theoretical and Applied Climatology 2015年第3期125卷 679-689页

作者： Gani, Abdullah Mohammadi, Kasra Shamshirband, Shahaboddin Khorasanizadeh, Hossein Seyed Danesh, Amir Piri, Jamshid Ismail, Zuraini Zamani, Mazdak Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Faculty of Mechanical Engineering University of Kashan Kashan Iran Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Water Engineering Soil and Water College University of Zabol Zabol Iran Advanced Informatics School Universiti Teknologi Malaysia Johor Bahru Malaysia

The availability of accurate solar radiation data is essential for designing as well as simulating the solar energy systems. In this study, by employing the long-term daily measured solar data, a neural network auto-regressive model with exogenous inputs (NN-ARX) is applied to predict daily horizontal global solar radiation using day of the year as the sole input. The prime aim is to provide a convenient and precise way for rapid daily global solar radiation prediction, for the stations and their immediate surroundings with such an observation, without utilizing any meteorological-based inputs. To fulfill this, seven Iranian cities with different geographical locations and solar radiation characteristics are considered as case studies. The performance of NN-ARX is compared against the adaptive neuro-fuzzy inference system (ANFIS). The achieved results prove that day of the year-based prediction of daily global solar radiation by both NN-ARX and ANFIS models would be highly feasible owing to the accurate predictions attained. Nevertheless, the statistical analysis indicates the superiority of NN-ARX over ANFIS. In fact, the NN-ARX model represents high potential to follow the measured data favorably for all cities. For the considered cities, the attained statistical indicators of mean absolute bias error, root mean square error, and coefficient of determination for the NN-ARX models are in the ranges of 0.44–0.61 kWh/m2, 0.50–0.71 kWh/m2, and 0.78–0.91, respectively.

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RETRACTED ARTICLE: Input Displacement Neuro-fuzzy Control and Object Recognition by Compliant Multi-fingered Passively Adaptive Robotic Gripper

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Journal of Intelligent & Robotic systems 2015年第2期82卷 177-187页

作者： Petković, Dalibor Shamshirband, Shahaboddin Anuar, Nor Badrul Sabri, Aznul Qalid Md Abdul Rahman, Zulkanain Bin Pavlović, Nenad D. Faculty of Mechanical Engineering Deparment for Mechatronics and Control University of Niš Niš Serbia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of History Faculty of Arts and Social Sciences Building University of Malaya Kuala Lumpur Malaysia

The requirement for new flexible adaptive grippers is the ability to detect and recognize objects in their environments. It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult make decision strategies using conventional techniques. Here, an adaptive neuro fuzzy inference system (ANFIS) for controlling input displacement and object recognition of a new adaptive compliant gripper is presented. The grasping function of the proposed adaptive multi-fingered gripper relies on the physical contact of the finger with an object. This design of the each finger has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize particular shapes of the grasping objects. Fuzzy based controllers develop a control signal according to grasping object shape which yields on the firing of the rule base. The selection of the proper rule base depending on the situation can be achieved by using an ANFIS strategy, which becomes an integrated method of approach for the control purposes. In the designed ANFIS scheme, neural network techniques are used to select a proper rule base, which is achieved using the back propagation algorithm. The simulation results presented in this paper show the effectiveness of the developed method.

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An efficient algorithm of information recommendation between groups in social networks

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2015年第6期43卷 1090-1093页

作者： Huang, Zhen-Hua Zhang, Bo Fang, Qiang Xiang, Yang Department of Computer and Technology Tongji University Shanghai201804 China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai200234 China

Information recommendation between groups is one of the most important ways for information sharing and transmitting in social networks. However, it needs exponential time cost to achieve the exact optimal recommendation solution. Hence this paper proposed an efficient algorithm EAOORS (Efficient Algorithm for Obtaining Optimal Recommendation Solution) which equivalently reduced this exponential time cost problem to extended steiner tree problem, and fast achieved the approximate optimal recommendation solution in the polynomial time complexity. The experimental result shows that the EAOORS algorithm is more efficient than the existing ones. ©, 2015, Chinese Institute of Electronics. All right reserved.

关键词： Approximation algorithms

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RETRACTED ARTICLE: Potential of support vector regression for solar radiation prediction in Nigeria

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Natural Hazards 2015年第2期77卷 1055-1068页

作者： Olatomiwa, Lanre Mekhilef, Saad Shamshirband, Shahaboddin Petkovic, Dalibor Power Electronics and Renewable Energy Research Laboratory (PEARL) Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Department of Electrical and Electronic Engineering Federal University of Technology Minna Nigeria Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department for Mechatronics and Control Faculty of Mechanical Engineering University of Niš Nis Serbia

In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taking from Iseyin meteorological station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration ( $$ \bar{n} $$ ). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R 2 with the polynomial function was 0.7395 and with the radial basis function, the R 2 was 0.5877.

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Designing an Intelligent system for Traffic Management

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通讯和计算机（中英文版） 2015年第3期12卷 123-127页

作者： Maha Rezzai Wafaa Dachry Fouad Moutaouakkil Hicham Medromi Systems Architecture Team Laboratory of Computer System and Renewable Energy University Hassan H Casablanca ENSEMCasablanca 20200 Morocco Laboratory of Mechanical Engineering Industrial Management and Innovation (IMMII) University Hassan I FST SettatMorocco

Traffic congestion has become a serious problem that arises in our cities; this is due to rapid population growth, the rapid increase in the number of cars. Therefore, there is an infernal traffic jams. It is in this light, it is imperative to eliminate or at least reduce traffic congestion through the adoption of the policy of ITS (intelligent transport systems). The objective of this paper is to propose a study on the problem of congestion in cities, by reducing traffic congestion.

关键词：智能系统交通管理交通拥堵设计智能交通系统汽车数量交通堵塞城市

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Convolution-based means of gradient for fast eye center localization

Convolution-based means of gradient for fast eye center loca...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hai-Bin Cai Hui Yu Chun-Yan Yao Shen-Yong Chen Hong-Hai Liu School of Computing University of of Portsmouth UK College of Computer Science Zhejiang University of Technology China College of Mechanical Engineering Zhejiang University of Technology China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University China

ISBN: (纸本)9781467372220

Localizing eye center is primary challenge for application-s involving gaze estimation, face recognition and human machine interaction. The challenge is caused by significant variability of eye appearance in illumination, shape, color, viewing angle and dynamics, and computation related issues. In this paper, we propose a convolution-based means of gradient method to efficiently and accurately locate the eye center in low resolution images. Priority of enhancing its computation is achieved by the use of FFT transform and fewer identified pixels of circular boundary of potential eye centres. The proposed algorithm is validated in the research database platform of BioID face database. The experimental results confirm that the proposed outperforms the-state-of-art methods and its potential in real-time eye gaze tracking related applications.

关键词： Convolution Eye center location Gradients Iris center location Convolution Eye Gradient mean gradient Human machine interaction

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Research scheduling problem of job-shop robotic manufacturing cell with several robots

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8918卷 119-123页

作者： Yang, Yujun Long, Chuanze Tao, Yu Key Laboratory of Computer Integrated Manufacturing System of Guangdong Province Institute of Mechanical& Electronic Engineering Guangdong University of Technology Guangzhou China

To solve the job-shop scheduling problem of robotic manufacturing cell with multiple robots, population initialization method and neighborhood search mechanism of its solution genetic algorithm are studied. The objective is to determine a schedule of machine and transport operations as well as assignment of robots to transport operation with minimize the maximum completion time. To improve the quality of the initial population, heuristic initialization method based on 3 vectors scheduling combining dispatching rules is proposed. Neighborhood structure is constructed based on the critical path. Experimental results show that the algorithm is effective. © Springer International Publishing Switzerland.

关键词： Genetic algorithms

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