The objectives of this research were to propose a model with some functions including CAR spatial effects and to select a proper model for predicting rince and rubber yields in southern provices of Thailand. A linear mixed model (LMM) with spatial effects and dummy varables and Fourier seasonal effects was proposed. Bayesian estimation was used and the estimated rice and rubber yields were used for prediction. The dependent variables were rice and rubber yields in southern provinces of Thailand. Factors considered were rain temperature soil fertilizer soil organic matter trend and also sesonal effects. The results show that rain temperature soil fertilizer soil organic matter trend and sesonal effects influence on rice and rubber yields. The proposed model with Fourier seasonal term is the most appropriate comparing to the model with dummy variable for season effects and the Holt-Winters model. Therefore the proposed model with Fourier sesaonal term should be the first consideration for prediction.

The objectives of this research were to propose a spatial analysis using Bayesian generalized linear mixed model for predicting drought in Thailand. The spatial effect was assumed to be a conditional autoregressive model (CAR model). The dependent variables was a drought or non-drought occurrence which was assumed to have a Bernolli distribution with logistic link function. Factors considered were rain temperature number of rainy days number of large reservoirs and number of medium reservoirs. The results show that the rain temperature number of rainy days number of large reservoirs and number of medium reservoirs influence on the drought occurrence. This study is useful for planning making decision preventing and remedying the drought problem.

Differential evolution is one of the most efficient optimization algorithms for solving complication problems including single objective multiobjective and many-objective optimization. It is a stochastic population-based search approach for optimization over the continuous space. The main advantages of differential evolution are simplicity robustness and high speed of convergence. The Advanced Fuzzy-based Multiobjective Differential Evolution (AFMDE) that exploits three performance metrics specifically hypervolume spacing and maximum spread to measure the state of the evolution process. The fuzzy inference rules are applied to these metrics in order to adaptively adjust the associated control parameters of the chosen mutation strategy used in AFMDE. The optimization algorithm will stop the evolution process if the number of iterations reaches the stopping criteria which usually is the maximum number of iterations. Then the optimization algorithm delivers the optimal solution founded. However sometimes if the maximum number of iterations is not appropriately defined the found solutions may not be the optimal ones. In case of the optimization algorithm has found the optimal solutions but it must continue the evolution process because the stopping criteria are not met. This can cause unnecessary using of high computational resources and time-consuming. Therefore this research study proposed the stopping criteria based on performance metrics feedback for AFMDE. The efficiency of the proposed criteria combined with AFMDE is evaluated on the well-known ZDT benchmark test suites.

In this paper proposed remote sensing using Normalized Difference Vegetation Index from NOAA STAR cluster value from k-means temperature rainfall number of rainy days and runoff to create runoff prediction model using Artificial Neural Network (ANN) and evaluated runoff models with the R2 and RMSE. The results show that the using of cluster value with other parameters to create predictive models can enhance forecasting results. When using Normalized Difference Vegetation Index with temperature value at lag time 1-2 month and cluster value at lag time 1 month to create model with ANN we have got the best performance which are RMSE=0.09 and R2=0.743. The experimental results shows that remote sensing data and cluster value from k-means can be used to predictive the runoff effectively.

This project report proposes a design and construction of model of protection equipment for three-phase transmission line by voltage relay for protect. By protection equipment can protect the transmission line from over voltage and under voltage on the transmission line The objective of design and construction model of protection equipment for three-phase transmission line. The objective for construction model of protection equipment for three-phase transmission line. For understand power system protection principles. And understand using to protection equipment for three-phase transmission line correct. From experimentation model of protection equipment could protect over voltage and under voltage on the transmission line