To solve a problem using Genetic Algorithms (GAs), a solution must be encoded into a binary string. The length of the binary string represents the size of the problem. As the length of the binary string increases, the size of the search space also increases at an exponential rate. To reduce the search space, one approach is to use a compressed encoding chromosome. This paper presents a genetic ...

This paper extends the work in [Suzuki, 1996] and presents an efficient depth-first branch­ and-bound algorithm for learning Bayesian network structures, based on the minimum description length (MDL) principle, for a given (consistent) variable ordering. The algorithm exhaustively searches through all network structures and guarantees to find the network with the best MDL score. Prelimi­ nary e...

The Minimum Description Length principle (MDL) can be used to train the hidden units of a neural network to extract a representation that is cheap to describe but nonetheless allows the input to be reconstructed accurately. We show how MDL can be used to develop highly redundant population codes. Each hidden unit has a location in a lowdimensional implicit space. If the hidden unit activities f...

This article introduces the concept of variable chromosome lengths in the context of an adaptive genetic algorithm (GA). This concept is applied to structural topology optimization with large numbers of design variables. In traditional genetic algorithms, the chromosome length is determined when the phenotype is encoded into a genotype. Subsequently, the chromosome length does not change. This ...

The Modeling with De Hoog and Laplace (MDL) Groundwater software is a contaminant transport-modeling program offering a suite of models suitable for simulating subsurface transport of contaminants (i.e., chromium and organics), biotracers, and microorganisms. The MDL Groundwater software provides solutions to a wide range of contaminant transport models that do not have closed-form analytical s...

in this paper, the optimal location and characteristics of tadas dampers in moment resisting steel structures, considering the application of minimum number of tadas dampers in a building as an objective function and the restriction for destruction of main members is studied. genetic algorithm in first generation randomly produces different chromosomes representing unique tadas dampers distribu...

This diploma thesis presents an unusual event recognition approach in the field of traffic surveillance. Such events are unusual traffic behaviour like traffic jams, accidents or ghost drivers. An interest-point based tracking algorithm (KLT-tracker) is discussed which pursues features on vehicles through a static camera scene. Tracking data can be collected by observing normal traffic. Then, t...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

In this paper, a signal processing method is proposed to estimate the low and high-frequency impedances of power systems using several short-term low power signal injections for a frequency range of 0-150 kHz. This frequency range is very important, and thusso it is considered in the analysis of power quality issues of smart grids. The impedance estimation is used in many power system applicati...

SUMMARY This paper addresses the problem of learning Bayesian belief networks (BBN) based on the minimum description length (MDL) principle. First, we give a formula of description length based on which the MDL-based procedure learns a BBN. Secondly, we point out that the diierence between the MDL-based and Cooper and Herskovits procedures is essentially in the priors rather than in the approac...