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Reducing users' fatigue and improving the performance are two focuses of the research of interactive evolutionary computation (IEC). Aiming at the focuses, knowledge learning in IEC is put forward. Before the discussion of knowledge learning, the issue of information sampled from history evolution is discussed, from which the knowledge is extracted. The knowledge learning based on gene-sense-unit...
Classification is one of the fundamental tasks of data mining, and many machine learning algorithms are inherently designed for binary (two-class) decision problems. Gene expression programming (GEP) is a genotype/phenotype genetic algorithm that evolves computer programs of different sizes and shapes (expression trees) encoded in linear chromosomes of fixed length. In this paper, we propose a novel...
With the rapid development of Internet, mobile-learning system has created new ways for educators to communicate with learners. Mobile-learning as a new mode of learning, the relationship between the study object and the subject and among the study main body and among the study object show multiple interaction and the construction, etc. This study model shows the advantages that the traditional model...
Decision tree is mainly used in classification and predictive model. The introduction of generalized decision tree (GDT) realized the unification of classification rules and decision tree structure. Meanwhile, a new method that based on DNA coding genetic algorithm to construct decision tree was proposed. It firstly classified dataset by C4.5 to get initial rule sets, then optimized the rule sets...
Software performance testing aims to discover faults related to QoS of a system, such as response time. This paper proposes a method to generate performance test cases automatically based on Genetic Algorithms for any system consisting of composite services. It considers users' experience in the performance test model. Based on the system's workflow, the usage pattern of a system is modeled as QoS-sensitivity...
In this paper, we explore the applicability of quantum-behaved particle swarm optimization (QPSO) algorithm, an efficient variant of particle swarm optimization (PSO) algorithm, to online system identification problems. First, quantum particle swarm optimization and particle swarm optimization are introduced. Then these two algorithms and genetic algorithms are applied to online identify parameters...
According to the characteristics of the consumer demands for pursuing relative product and service in the environment of electronic commerce, it has been firstly set up in the paper that the consumer demands proxy system which is based on multi-agent technology. Then the system is analyzed in great details: the relevant consumer models related to variable demand of consumers on Internet have been...
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