Issue 2 • May 2005
Table of contentsPublication Year: 2005, Page(s): c1| PDF (42 KB)
IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews publication informationPublication Year: 2005, Page(s): c2| PDF (34 KB)
Guest Editorial Special Issue on Knowledge Extraction and Incorporation in Evolutionary ComputationPublication Year: 2005, Page(s):129 - 130
Cited by: Papers (2)
Cited by: Papers (11)
This paper presents a distributed coevolutionary classifier (DCC) for extracting comprehensible rules in data mining. It allows different species to be evolved cooperatively and simultaneously, while the computational workload is shared among multiple computers over the Internet. Through the intercommunications among different species of rules and rule sets in a distributed manner, the concurrent ... View full abstract»
Cited by: Papers (43)
An agent-based evolutionary approach is proposed to extract interpretable rule-based knowledge. In the multiagent system, each fuzzy set agent autonomously determines its own fuzzy sets information, such as the number and distribution of the fuzzy sets. It can further consider the interpretability of fuzzy systems with the aid of hierarchical chromosome formulation and interpretability-based regul... View full abstract»
Cited by: Papers (35)
Features represent the characteristics of objects and selecting or synthesizing effective composite features are the key to the performance of object recognition. In this paper, we propose a coevolutionary genetic programming (CGP) approach to learn composite features for object recognition. The knowledge about the problem domain is incorporated in primitive features that are used in the synthesis... View full abstract»
Cited by: Papers (21)
This paper describes a unified network synthesis approach for the conceptual stage of mechatronic systems design using bond graphs. It facilitates knowledge interaction with evolutionary computation significantly by encoding the structure of a bond graph in a genetic programming tree representation. On the one hand, since bond graphs provide a succinct set of basic design primitives for mechatroni... View full abstract»
Cited by: Papers (96)
We present an overview of evolutionary algorithms that use empirical models of the fitness function to accelerate convergence, distinguishing between evolution control and the surrogate approach. We describe the Gaussian process model and propose using it as an inexpensive fitness function surrogate. Implementation issues such as efficient and numerically stable computation, exploration versus exp... View full abstract»
Cited by: Papers (49)
Since the Estimation of Distribution Algorithm (EDA) was introduced, different approaches in continuous domains have been developed. Initially, the single Gaussian distribution was broadly used when building the probabilistic models, which would normally mislead the search when dealing with multimodal functions. Some researchers later constructed EDAs that take advantage of mixture probability dis... View full abstract»
Cited by: Papers (7) | Patents (1)
Data mining is an information extraction process that aims to discover valuable knowledge in databases. Existing genetic algorithms (GAs) designed for rule induction evaluates the rules as a whole via a fitness function. Major drawbacks of GAs for rule induction include computation inefficiency, accuracy and rule expressiveness. In this paper, we propose a constraint-based genetic algorithm (CBGA)... View full abstract»
An evolutionary algorithm for solving nonlinear bilevel programming based on a new constraint-handling schemePublication Year: 2005, Page(s):221 - 232
Cited by: Papers (86)
In this paper, a special nonlinear bilevel programming problem (nonlinear BLPP) is transformed into an equivalent single objective nonlinear programming problem. To solve the equivalent problem effectively, we first construct a specific optimization problem with two objectives. By solving the specific problem, we can decrease the leader's objective value, identify the quality of any feasible solut... View full abstract»
Cited by: Papers (164)
A common approach to constraint handling in evolutionary optimization is to apply a penalty function to bias the search toward a feasible solution. It has been proposed that the subjective setting of various penalty parameters can be avoided using a multiobjective formulation. This paper analyzes and explains in depth why and when the multiobjective approach to constraint handling is expected to w... View full abstract»
Cited by: Papers (22)
In this paper, an evolutionary fuzzy neural network using fuzzy logic, neural networks (NNs), and genetic algorithms (GAs) is proposed for financial prediction with hybrid input data sets from different financial domains. A new hybrid iterative evolutionary learning algorithm initializes all parameters and weights in the five-layer fuzzy NN, then uses GA to optimize these parameters, and finally a... View full abstract»
Cited by: Papers (5)
A genetic recurrent fuzzy system which automates the design of recurrent fuzzy networks by a coevolutionary genetic algorithm with divide-and-conquer technique (CGA-DC) is proposed in this paper. To solve temporal problems, the recurrent fuzzy network constructed from a series of recurrent fuzzy if-then rules is adopted. In the CGA-DC, based on the structure of a recurrent fuzzy network, the desig... View full abstract»
Cited by: Papers (9)
The increasing amount of information available is encouraging the search for efficient techniques to improve the data mining methods, especially those which consume great computational resources, such as evolutionary computation. Efficacy and efficiency are two critical aspects for knowledge-based techniques. The incorporation of knowledge into evolutionary algorithms (EAs) should provide either b... View full abstract»
Cited by: Papers (25)
In this paper, we propose a novel method for solving multiobjective optimization problems using reduced models. Our method, called objective exchange genetic algorithm for design optimization (OEGADO), is intended for solving real-world application problems. For such problems, the number of objective evaluations performed is a critical factor as a single objective evaluation can be quite expensive... View full abstract»
A comparative study of three evolutionary algorithms incorporating different amounts of domain knowledge for node covering problemPublication Year: 2005, Page(s):266 - 271
Cited by: Papers (17)
This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ extra heuristic knowledge. In theory, it is proven that all three algorithms can find an optimal solution in finite generations and find a feasible solution efficiently; but none of the... View full abstract»
Special issue on interdependencies in civil infrastructure systemsPublication Year: 2005, Page(s): 272| PDF (125 KB)
IEEE Systems, Man, and Cybernetics Society InformationPublication Year: 2005, Page(s): c3| PDF (25 KB)
IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews Information for authorsPublication Year: 2005, Page(s): c4| PDF (33 KB)
Aims & Scope
This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Human-Machine Systems.
Overview, tutorial and application papers concerning all areas of interest to the SMC Society: systems engineering, human factors and human machine systems, and cybernetics and computational intelligence.
Authors should submit human-machine systems papers to the IEEE Transactions on Human-Machine Systems.
Authors should submit systems engineering papers to the IEEE Transactions on Systems, Man and Cybernetics: Systems.
Authors should submit cybernetics papers to the IEEE Transactions on Cybernetics.
Authors should submit social system papers to the IEEE Transactions on Computational Social Systems.
Meet Our Editors
Dr. Vladimir Marik
(until 31 December 2012)