The purpose of this research the study of the potential of Suphanburi area for planting investment. In which the researcher has studied the soil data set that is different in each area of Suphanburi. That is quite diverse if divided by each district in Suphanburi province themselves from the basic information report in Suphanburi and the agricultural information of Suphanburi for the year 2017 when comparing with the soil set of Suphanburi it can be seen that the cultivation is quite comprehensive all. The researcher created a model. Mathematical model to calculate production costs and forecasting of plants suitable for cultivation According to the potential of Suphanburi area. In the form of a website for ease of use as much as possible.

The objectives of this research are to propose an approate and efficient model for analyzing rice corn and sugar yields data. A linear mixed model (LMM) with spatial correlation following the conditional autoregressive model (CAR) was adopted. The results show that for rice yields if the amount of rainfall in a harvest season increases 1 mm the yields will decease by 25.74 tons. if the temperature in the harvest season increases 1 Celsius the yields will decease by 212.60 tons and according to the trend the yield will increase by 15.80 tons each year. For sugar cane yields if the amount of rainfall in the harvest season increases 1 mm the yields will decease by 51.35 tons. if the temperature in the harvest season increase 1 Celsius the yields will incease by 121.30 tons and according to the trend the yield will increase by 29.93.80 tons each year. For corn yield if the amount of rainfall in the havest season increases 1 mm the yields will incease by 73.45 tons. if the temperature in he havest season increases 1 celsius the yields will decease by 40.44 tons and according to the trend the yield will increase by 1.74 tons each year.

This paper presents a mathematical modelling for design the control system of a liquid. The system are consists of one and two tanks of a liquid. To confirm the achieved mathematical modelling is used to design P PI PD and PID controller in the frequency domain. The experimental results are indicated as the following. An one tank of a liquid controlling The controller can be control the liquid level to set point with in 100s. In the case of a disturbance occurs in the system it is perform by drain a liquid. As same as the controller it can be control the liquid level into the steady state. In the part of the liquid control this is the interaction between two tanks. The experimental results of the system operation the controller can be control the liquid into the set point both occur disturbance and without disturbance respectively

Blends of R22/R152a/R124 have been proposed to replace R12 in refrigeration systems.In this research work a technique to simply evaluate thermodynamic properties of refrigerant mixtures has been developed from Raoults Law.the method has been approached to evaluate the properties of the refrigerant blends avalable in the market such as MP39( R22/R152/R124 53/13/34)MP52 (R22/R152a/R124 33/15/52)and MP66 (R22/R152/R124 61/11/28) .The results agree well with those given by the manufacture within 5 % error The method has also been used to evaluate the properties of the ( R32/R125/R134a 23/25/52)refrigerant agree wall with those given from the manufacture with in 3 % error The thermodynamic property dlagrams of these refrigerant blends are also proposed.

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.