Petrochemicals industry is one of the major industries in modern economy. Almost all synthetic chemicals or materials are related. Ethylene is the main product of this industry, which is produced from naphtha cracker. Butadiene is a by-product of naphtha cracking, but it is the most important raw material of synthetic rubbers. Most synthetic rubber plants do not have their own butadiene plant. All the materials were supplied from up-stream crackers. Due to the unstable supply and price surge recently, the cost of butadiene is higher than 70% of the total production cost in synthetic rubbers manufacturing. Huge price fluctuation in butadiene caused a big financial loss in 2008. These economic situations have made the price prediction an important issue for synthetic rubber manufacturers. In this research, we reviewed the historical price data of crude oil, naphtha, ethylene, propylene, butadiene and MTBE from the upper stream of petrochemicals in supply and the price of nature rubber, synthetic rubbers in demand. This study intends to find the petrochemicals price variation factors and uses butadiene as example. ¡§Time series¡¨ and OLS methods are used to build price prediction models to explain the price fluctuation in the past. Our research has found that the monthly price of butadiene is highly related to last month¡¦s price of butadiene, crude oil price and even related to last 9 month butadiene price. This may be because of the regular economical circulation and naphtha crackers annual turn around. The price of spot trading is related to the last week¡¦s price of butadiene and its co-product propylene. Those findings are valuable for synthetic rubber manufacturer in raw material procurement.

An ecosystem always involves some implicit relations between habitat environment and inhabitants, whose reciprocal links can not be identified easily. Three sets of ecological monitoring data were analyzed in this study, including coral reef, algae (Thalassia hemprichii Aschers) in Kenting National Park, and Formosan landlocked salmon (Oncorhynchus masou formosanus) in the basin of Chichiawan Stream. Two data-oriented analysis techniques, which are Habitat Evaluation Procedure (HEP) and Group Method of Data Handling (GMDH), were applied to retrieve the embedded patterns from these data sets. Eventually, for each data set, a forecasting model based on the technique of combined forecasting were developed, which is to integrate the results from HEP and GMDH, for improving the overall modeling precision. The results of this study show that the data-oriented analyses, such as HEP and GMDH, are useful for finding valid information from the ecological data. Furthermore, the combined forecasting technique can really improve the performance of model prediction even for the ecological research. In order to acquire the most important habitat environmental factors affecting the inhabitants, this study also performed sensitivity analysis of the models. The contributions of this study are to identify effective knowledge for future ecological research and to provide reasonable suggestions for formulating conservation strategy.