Nootyasakool, Supakit
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Nootyasakool, Supakit
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Nootyaskool, Supakit
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supakit.no@kmitl.ac.th
14 results
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Item type:Publication, Hybrid Genetic Algorithm with Baum-Welch Algorithm by using diversity population technique(2006-12-01); Kruatrachue, BoonteeBaum-Welch Algorithm (BWA) have used in recognition systems, many researchers have improved BWA performances by using Hybrid Genetic Algorithm (HGA). This paper presents a new HGA technique by using diversity population structure. We surveyed HGA techniques and divided into four types. There were separate processes, population types, fitness determiners, and diversity population structure. A technique of diversity population structure protected applying BWA to similar population. Different population structures make available GA to find optimum point quickly. This paper compared all of HGA techniques, which there trained on Hidden Markov Models (HMM), in an application Thai off-line handwritten recognition, we used database from NECTEC. An experiment of HGA, HMM probability of diversity population techniques get better than techniques of population types 52.65% improvement and there better than techniques of separately process 37.91% improvement. Moreover, HGA experimented five times repeatedly, standard derivation value of diversity population techniques showed closely results. © 2006 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Reinforcement learning applied to scrum team towards large-scale global optimization(2019-02-02); Ounsrimuang, PimolratLarge-scale problems have size of problem over a thousand dimensions in finding a best solution that uses long computation times. In this work, we use an idea of scrum methodology that is a well-known in software development companies, to create an optimization algorithm. The scrum methodology describing about the team organization likes as rugby team management that player have expert in game. The proposed algorithm is developed based on concept of the evolutionary computation by this work added agent specifics in leaning environment of the problem. The specific of the agent is reinforcement learning by taking an action and getting reward. The proposed algorithm was experimented on a large-scale global optimization finding optimum point of numerical function, comparing between with and without reinforcement learning. The experiment result showed that the usage of reinforcement learning has good results. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, HMM Parameters Optimization using Combine Genetic Algorithm and Iterative Training(2003-12-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predicting Fuel Burn with Neural Network to Adjust Contingency Fuel of Airplane(2023-01-01); ; The amount of fuel in an airplane tank is very important for flying. however, flying a short distance by adding a fuel-full tank is not energy efficient because spending a lot of tons for holding fuel weight. The flight planners who consider the amount of fuel to add to the tank by using historical data, use fuel burn calculating and adjust contingency fuel. This research presents the neural networks to predict fuel burn, which learn from historical airplane data. The experiment applied to local and international flight data and used both Airbus and Boeing. The predicted model was swapped and tested on the outbound and inbound replacements for confirmation capable of the predicted mode. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Gold Investment Model on RNN and Finding Best Investment Strategy on PSO(2022-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Roulette wheel selection applied to PSO on numerical function in discrete and continuous space(2016-07-22) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hidden Markov Models predict foreign exchange rate(2015-01-15); Choengtong, WuttichowThis paper presents the prediction Thai baht by using Hidden Markov Models (HMM) with which the prediction model uses four factors, dollar index, interest rate, inflation rate and economic growth. The main idea of this work is a technique of encoding four factors into one observation sequence to train HMM. One result of prediction data will present four factors after decoding. The experiment is done using the data-by-day from 2002 to 2013 and showed that the technique has the mean percentage error of 0.167% to predict Thai currency exchange. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The hybrid implementation genetic algorithm with particle swarm optimization to solve the unconstrained optimization problems(2012-10-26)Genetic algorithm (GA) has an advantage in exploration search. Particle swarm optimization (PSO) has an advantage in sharing movement information between particles. The combining between GA and PSO is proposed in this research. We design hybrid-GA with PSO, and compare the performance with simple GA and simple PSO, which their models will find the solution of five-difference complexity of numerical functions. The experiment result showed that hybrid GA with PSO can find the solution of a multimodal problem and unimodal with noise signal quickly. © 2012 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparison solving discrete space on flower pollination algorithm, PSO and GA(2016-03-23) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Categorize Level of Crystal Sugar Making with Recurrent Neural Network(2022-01-01)