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【期刊论文】Behavioral Modeling With New Bio-inspired Coordination Generalized Molecular Model Algorithm
冯翔, Francis C.M. Lau, 虞慧群
Information Sciences,2013,252(12):1-19
2013年11月10日
Social Networks (SN) is an increasingly popular topic in artificial intelligence research. One of the key directions is to model and study the behaviors of social agents. In this paper, we propose a new computational model which can serve as a powerful tool for the analysis of SN. Specifically, we add to the traditional sociometric methods a novel analytical method in order to deal with social behaviors more effectively, and then present a new bio-inspired model, the coordination generalized molecule model (CGMM). The proposed analytical method for social behaviors and CGMM are combined to give an algorithm that can be used to solve complex problems in SN. Traditionally, SN models were mainly descriptive and were built at a very coarse level, typically with only a few global parameters, and turned out to be not sufficiently useful for analyzing social behaviors. In this work, we explore bio-inspired analytical models for analyzing social behaviors of intelligent agents. Our objective is to propose an effective and practical method to model intelligent systems and their behaviors in an open and complex unpredictable world.
Social networks(SN), Social behavior, Social coordination, Coordination generalized molecule model(, CGMM),
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【期刊论文】An Improved Group Search Optimizer for the Internet of Things
冯翔, 刘晓婷, 虞慧群
International Journal of Communication Systems,2014,29(3):535-552
2014年10月24日
The development of the Internet of Things brings new opportunities and challenges for sensor networks.The scale of sensor networks tends to be larger. And the fusion rules need to be intelligent. In this paper, we propose a new Internet of Things group search optimizer (ITGSO) to solve intelligent information fusion problems in the high-dimensional multi-sensor networks. ITGSO is inspired by the latest research achievement about leader decision in Nature and works about social coordination, which mainly consists of three parts: basic group search optimizer, binary group search optimizer and social decision model. With ITGSO, we need less time to obtain minimum Bayes cost than particle swarm optimization. And information of uncertain social intelligent problems can be fused. In this paper, we give the theoretical basic of ITGSO and proved its validity via mathematical analysis and simulation results.
Internet of Things group search optimizer, sensor network, binary group search optimizer, leader decision
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【期刊论文】Group Mosquito Host-Seeking Algorithm
冯翔, 刘晓婷, 虞慧群
Applied Intelligence,2015,44(3):665-686
2015年11月04日
The host-seeking behavior of mosquitoes is very interesting. This paper is motivated by the following general observation on mosquito groups and their host-seeking behavior in nature: (1) Mosquitoes’ behavior has possession of the parallelism, openness, local interactivity and self-organization. (2) Mosquito groups seek host very fast. (3) The host-seeking behavior is similar to the producerscrounger process, which assumes that group members search either for “finding” (producer) or for “joining” (scrounger) opportunities. It stimulates us to extend a mosquito system model in nature to group mosquito hostseeking model (GMHSM) and algorithm (GMHSA) for intelligent computing. In this paper, we propose GMHS approach and show how to use it. By GMHSM, the TSP is transformed into the kinematics and dynamics of mosquito groups host-seeking process. The properties of GMHSM and GMHSA, including the correctness, convergence and stability, have been discussed in this paper. The GMHS approach has many advantages in terms of multiple objective optimization, large-scale distributed parallel optimization, effectiveness of problem-solving and suitability for complex environment. Via simulations, we test the GMHS approach and compare it with other state-of-art algorithms.
Group Mosquito Host-Seeking Model (, GMHSM), and algorithm (, GMHSA), , Leader decision, Traveling Salesman Problem (, TSP), , Distributed and parallel algorithm
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【期刊论文】 A Novel Optimization Algorithm Inspired by the Creative Thinking Process
冯翔, 邹儒, 虞慧群
Soft Computing,2014,19(10):2955-2972
2014年09月19日
Creative thinking, which plays an essential role in the progress of human society, has an outstanding problem-solving ability. This paper presents a novel creativity-oriented optimization model (COOM) and algorithm (COOA) inspired by the creative thinking process. At first, COOM is constructed by simplifying the procedure of creative thinking while retaining its main characteristics. And then, COOA is presented for continuous optimization problems. It is a realization of COOM. As a new nature-inspired algorithm, COOA is different from other similar algorithms in terms of the basic principle, mathematical formalization and properties. Features of the COOM and the corresponding algorithm include a powerful processing ability for the complex problems, namely high-dimensional, highly nonlinear and random problems. The proposed approach also has the advantages in terms of the higher intelligence, effectiveness, parallelism and lower computation complexity. The properties of COOA, including convergence and parallelism, are discussed in detail. The numerous simulations on the CEC-2013 real-parameter optimization benchmark functions’ problems have shown the effectiveness and parallelism of the proposed approach.
Creativity-oriented optimization algorithm, Nature-inspired algorithm, Creative thinking, Numerical function optimization
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【期刊论文】Crystal-Energy Optimization Algorithm
冯翔, 马美怡, 虞慧群
Computational Intelligence,2014,32(2):284-322
2014年11月28日
Nature has always been a muse for those who dream in art or science. As it goes, optimization algorithms inspired by nature have been widely used to solve various scientific and engineering problems because of their intelligence and simplicity. As a novel nature-inspired algorithm, the crystal energy optimizer (CEO) is proposed in this article. The proposed CEO is motivated by the following general observation on lake freezing in nature: the dynamics of crystals have possession of parallelism, openness, local interactivity, and self-organization. It stimulates us to extend a crystal dynamic model in physics to a generalized crystal energy optimizer for traveling salesman problems, so as to exploit the advantages of crystal dynamic system and to realize the aforementioned purposes. The proposed CEO has these advantages: (1) it has the ability to perform large-scale distributed parallel optimization; (2) it can converge and avoid local optimum; and (3) it is flexible and easy to adapt to a wide range of optimization problems
crystal energy optimizer (, CEO), , omputational intelligence, parallel algorithm, nature-inspired algorithm, traveling salesman problem (, TSP),
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