In this work solar erythemal ultraviolet radiation (EUV) which affects human skin and skin cancer was investigated at Songkhla province (7.2°N 100.6°E). EUV was converted to UV index then the data was used for model development and forecasting of hourly UV index using Artificial Neural Network (ANN). The ANN model has one input layer two hidden layers and one output layer. This input layer consists of extraterrestrial erythemal ultraviolet radiation solar zenith angle aerosol optical depth and cloud index which affect ultraviolet radiation and the output layer is hourly UV index. The results show that hourly UV index obtained from ANN and that from the measurement are in reasonable agreement with root mean square difference of 12.8% and mean bias difference of -2.4%. For forecasting of the hourly UV index the data for 7 days earlier was used for forecasting the next UV index for one day or nine-hour (08:00 am.-16:00 pm.). Multi-layer perceptron and back propagation algorithm were used in the model forecasting. The results show that the UV index from the model forecasting is reasonable agrees with UV index from measurement with root mean square difference of 17.0% and mean bias difference of 0.3%.

he monthly rainfall forecasts are very important in Thailand because the most of people has a career in agriculture. The monthly rainfall forecasts can be analyzed for manage water resources. In addition the monthly rainfall forecasting is used to manage water for consume in Thailand. This research is forecasting monthly rainfall under the global warming using a multilayer neural network. It is a network with one hidden layer. The data from the Meteorological Department is use. Imported variables include temperature humidity and wind. The forecast from January to December 2018. The mean square error (MSE) to measure forecasting accurate and found that the value is suitable error (10.25). The neural network can provide accurate monthly rainfall forecasts from January to December. It was found that the southern region had the highest rainfall and the eastern region northeastern region northern region central and western regions respectively. Therefore neural networks can be forecast rainfall accurately and efficiently. It can be used to analyze and manage water resources effective.

This research aims to develop the coconut coir and fiber indoor acoustic and thermal insulation boards mixed with natural latex. The 5 ratios of coconut coir: coconut fiber: natural rubber were equal to 0.1: 0.9: 0.1 0.1: 0.9: 0.15 0.1: 0.9: 0.2 0.1: 0.9: 0.25 and 0.1: 0.9: 0.3 by weight. The indoor acoustic and thermal insulation boards were produced by knitting the coconut coir and fiber spraying the natural latex and heat compressing. The properties testing of indoor acoustic and thermal insulation boards included the density test water absorption test tensile strength test thermal conductivity test sound protection efficiency test and real usage test. From the results 0.1: 0.9: 0.15 ratio is the most suitable ratio of coconut coir and fiber indoor acoustic and thermal insulation board mixed with natural latex. The natural latex which putted in these indoor acoustic and thermal insulation boards can reduce the water absorption and increase tensile strength and sound protection efficiency.

The results of the experiments were found that the temperature of the castings was higher than that of the silver alloys. The workpiece temperature is 500C the workpiece is good 26%. The workpiece is 74%. The temperature is 550C. The workpiece is 26%. The workpiece is 74%. The temperature is 600C. The workpiece is 40%. The workpiece is 60%. The workpiece is a fin. There are many factors that cause fins on the workpiece. Use of low-strength mortar In addition the use of excessive compression or heat transfer resulting in the expansion and shrinkage is not equal. This causes the cracking of the metal water to expand at a temperature of 650 ° C. The fine specimen 56% of the workpiece loses 44%. This temperature results in the smallest workpiece caused by the uneven surface. Cause of the cooling rate in each part of the casting is not equal. And at 700 degrees Celsius it is best to cast silver ornaments with pink color because the results show that the work is minimal. There are 70% good work piece 30%

The results of the study on the optimum temperature for baking soda extinguishers were investigated. B9R-3-EMERALD Using brass material in experiments. It was found that the temperature of 750˚C was good for 48% of the workpiece 52% was found that the workpiece was damaged at the surface of the work very porous at the surface. Caused by the heat of metal water pouring into contact with the moisture of the mold resulting in gas. High temperature of metal water Or eliminate gas in metal water is not exhausted. The workpiece is not suitable at a temperature of 800 ° C with a good workpiece of 76%. The workpiece loses 24%. The workpiece loses less punch at the lower porosity as well at 750˚C in temperature. 850˚C workpiece 96% workpiece 4% workpiece the workpiece is almost out. It is less than 750˚C and 800˚C at porosity. And at 900˚C the workpiece is 100% of the workpiece 0%. The workpiece is the best. Workpiece waste from the minimum. The test results make the temperature at 900 ° C is the cleanest casing temperature