Constraint satisfaction on dynamic environments by the means of coevolutionary genetic algorithms

We discuss adaptability of evolutionary computations in dynamic environments. We introduce two classes of dynamic environments which are utilizing the notion of constraint satisfaction problems: changeover and gradation. The changeover environment is a problem class which consists of a sequence of the constraint networks with the same nature. On the other hand, the gradation environment is a problem class which consists of a sequence of the constraint networks such that the sequence is associated with two constraint networks, i. e., initial and target, and all constraint networks in the sequence metamorphosis from the initial constraint network to the target constraint network. We compare coevolutionary genetic algorithms with SGA in computational simulations. Experimental results on the above dynamic environments confirm us the effectiveness of our approach, i.e., coevolutionary genetic algorithm</p

A new fitness function for discovering a lot of satisfiable solutions in constraint satisfaction problems

In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety of instances of general constraint satisfaction problems demonstrate the effectiveness of the proposed fitness function</p

Design and implementation of OFDM signal processing on PSoC microcontroller

Article2013 International Conference on ICT Convergence (ICTC). 391-392 (2013)journal articl

Estimation of Bayesian network algorithm with GA searching for better network structure

Estimation of Bayesian network algorithms, which adopt Bayesian networks as the probabilistic model were one of the most sophisticated algorithms in the estimation of distribution algorithms. However the estimation of Bayesian network is key topic of this algorithm, conventional EBNAs adopt greedy searches to search for better network structures. In this paper, we propose a new EBNA, which adopts genetic algorithm to search the structure of Bayesian network. In order to reduce the computational complexity of estimating better network structures, we elaborates the fitness function of the GA module, based upon the synchronicity of specific pattern in the selected individuals. Several computational simulations on multidimensional knapsack problems show us the effectiveness of the proposed method.</p

Perception-action rule acquisition by coevolutionary fuzzy classifier system

Recently, many researchers have studied the techniques in applying a fuzzy classifier system (FCS) to control mobile robots, since the FCS can easily treat continuous inputs, such as sensors and images by using a fuzzy number. By using the FCS, however, only reflective rules are acquired. Thus, in the proposed approach, an additional genetic algorithm is incorporated in order to search for strategic knowledge, i.e., the sequence of effective activated rules in the FCS. Therefore, the proposed method consists of two modules: an ordinal FCS and the genetic algorithm. Computational experiments based on WEBOTS, one of the Khepera robot simulators, confirm the effectiveness of the proposed method</p

Coevolutionary GA with schema extraction by machine learning techniques and its application to knapsack problems

The authors introduce a novel coevolutionary genetic algorithm with schema extraction by machine learning techniques. Our CGA consists of two GA populations: the first GA (H-GA) searches for the solutions in the given problems and the second GA (P-GA) searches for effective schemata of the H-GA. We aim to improve the search ability of our CGA by extracting more efficiently useful schemata from the H-GA population, and then incorporating those extracted schemata in a natural manner into the P-GA. Several computational simulations on multidimensional knapsack problems confirm the effectiveness of the proposed method</p

Adaptive control based on theoretical analysis in RC-OFDM systems

Article2013 International Conference on ICT Convergence (ICTC). 581-582 (2013)journal articl

Robustness against fading fluctuation in Hermite-symmetric subcarrier coding for OFDM systems

Article2014 International Conference on Information and Communication Technology Convergence (ICTC). 834-835 (2014)journal articl

Bofutsushosan, an Oriental Herbal Medicine, Attenuates the Weight Gain of White Adipose Tissue and the Increased Size of Adipocytes Associated with the Increase in Their Expression of Uncoupling Protein 1 in High-Fat Diet-Fed Male KK/Ta mice

Bofutsushosan (BOF), an oriental herbal medicine, has been used as an anti-obesity drug in overweight patients. In the present study, to evaluate the anti-obesity and anti-diabetic effects of BOF, we investigated the effects of BOF on the white adipose tissue (WAT) weight, the size of adipocytes, adiponectin expression, and oral glucose tolerance test results in high-fat diet-fed male KK/Ta mice. In addition, the mRNA expression levels of uncoupling protein 1 (UCP1) and UCP2 mRNA in WAT and brown adipose tissue (BAT) were measured. 6-week-old KK/Ta mice were divided into four groups and fed a purified powdered basal diet (the BD group), a purified high-fat (HF) powdered diet containing suet powder at 37.5 g/100 g diet (the HF group), a high-fat diet plus 1.0% bofutsushosan (BOF) treatment (the HF + BOF group), or a high-fat diet plus 1.0% daisaikoto (DAI) treatment (the HF + DAI group) for 4 weeks. The weight of WAT and the size of adipocytes were increased in the HF group compared with those in the BD group, and these increases in the HF group were significantly inhibited in the HF + BOF group, but not affected in the HF + DAI group. There were no statistically significant differences in plasma levels and tissue mRNA levels of adiponectin among the four groups. There were no significant differences in UCP1 mRNA expression of BAT among the four groups. The expression of UCP1 mRNA in WAT was found in the HF + BOF group, but little expression was seen in the WAT of the BD, HF, or HF + DAI groups. The elevated plasma glucose levels and responses after the glucose loading in the HF group tended to decrease in the HF + BOF group. These results suggest that BOF decreases the weight and size gains of WAT along with up-regulating UCP1 mRNA in WAT in high-fat diet-fed mice

A Mouse Model of Metabolic Syndrome; Increase in Visceral Adipose Tissue Precedes the Development of Fatty Liver and Insulin Resistance in High-Fat Diet-Fed Male KK/Ta Mice

To determine the relative contribution of obesity and visceral white adipose tissue (WAT) to metabolic syndrome, we developed a model that is susceptible to high-fat diet-induced obesity and insulin resistance using male KK/Ta mice. The ratio of WAT weight to body weight was greater in the high-fat diet group compared with the control group in 10-, 14-, and 22-week-old mice. The increase in visceral WAT preceded development of fatty liver and insulin resistance. Adiponectin mRNA expression in WAT was markedly decreased before the decrease in its plasma levels or the development of insulin resistance. Insulin resistance appeared in association with fatty infiltration and TNF-α expression in the liver in 22-week-old mice. These data indicate that our mouse model would be useful for future studies that investigate the role of visceral WAT and its products in the development of metabolic syndrome