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The characteristic data applied for establishing predicting models of pipe failure in water distribution system (WDS) should be examined and screened in the first place. The effects of different way of data processing based on a series on maintenance records are compared, which includes a classification method by Bayesian theorem, a hypothesis testing by analysis of variance and an association rule...
The objective of this paper is to study the relationships among the significant parameters impacting CO2 production. An enhanced understanding of the intricate relationships among the process parameters enables prediction and optimization, thereby improving efficiency of the CO2 capture process. Our modeling study used the operational data collected over a 3-year period from the amine-based post combustion...
This paper analyzed some existing problems of the present air-cargo forecast methods. Then it established the SVM (support vector machine) model for air-cargo demand forecasting. Taking the historical statistical data of Beijing to Shanghai cargo volumes from Jan-2005 to Mar-2006 as fitting and forecasting specimens, we can obtain the prediction model to optimize, which was compared with that of Brown...
Quality control in the food industry is often performed by measuring various chemical compounds of the food involved. We propose an imaging concept for acquiring high quality multispectral images to evaluate changes of carrots and celeriac over a period of 14 days. Properties originating in the surface chemistry of vegetables may be captured in an integrating sphere illumination which enables the...
In the wire bonding process, different combinations of parameter values will directly affect wire bonding quality. The optimal combination of these parameter values is very important to ensure the overall process quality response. Therefore, it is necessary to investigate the effects and interactive relationship of the bonding parameters on the bonding quality. This paper chooses the response factors...
In this work we present an instance of an architecture for the development of robust evolving predictive models. The architecture provides a conceptual framework for the development of such models while at the same time it provides mechanisms for the minimisation of effort needed for the development and maintenance of the models. These mechanisms deal with the model and parameter selection, model...
In this paper, the efficiency of neuro fuzzy network (ANFIS) is examined against auto regression (AR). Mean absolute percentage error (MAPE) is applied for this purpose. After applying different data preprocessing methods, the models are developed. A method for calculating ANFIS performance is also proposed. Due to various seasonal and monthly changes in oil production and difficulties in modeling...
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