Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
The nature of statistical learning theory
The nature of statistical learning theory
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper analyses several currently used computing methods inspired by the nature and concludes their common properties and their disadvantages. It then proposes a more abstract computing model inspired by the nature according to theoretical results on number theory. We also present a good lattice points method based on the number theory for problem solving, of which the discrepancy of the new method is minimized in the sense when the number of points are fixed. This method is dimensional independent and can be used to solve high dimensional problems. A typical algorithm is proposed to apply Genetic Algorithm and Immume Algorithm. Some comparable examples are given to show the advantages of our new method.