Papers by Keyword: Target Value

Abstract: In this paper, the data mining technology and the mining process was explained; and several common methods of data mining were described. Based on the characteristics of the target value, application of text classification and textual association in the target value mining were discussed, and the process model of data mining concerning target value was also expressed.

Abstract: With the rapid economic development, China is experiencing increased land contamination and lead poisoning problem in recent years, which is no longer restricted to isolated incidents and locations. There is an urgent need to remediate the lead contaminated soils to protect the publics health. However, contaminated land remediation and determination of remediation target value has been neglected for years. In order to accommodate uncertainties within the conservative point estimation of remediation target value for lead contaminated soils, Monte Carlo simulation technique is integrated into the traditional calculation model from a probabilistic perspective. Risk-based remediation target values for lead contaminated soils of different land use types (including school/hospital, residential, business and industrial use) are developed preliminarily. Furthermore, this study highlights the necessity to determine the remediation target value on the basis of actual (i.e. site-specific) risks to humans and, besides, actual risks due to contaminant migration.

Abstract: Handwritten numeral recognition is an important branch in the field of pattern recognition, has broad application prospects. This article presents a method of using BP Neural Network to implement programme for recognition of free handwritten numerals. Scanned handwritten numeral image after preprocessing and feature extraction, classificated and recognized by the BP Neural Network. Through Matlab simulation experiments it shows that the recognition method is effective and has high recognition rate.

Abstract: The author wants to use a case study to investigate the injection moulding machine parameters which will affect the horizontal length dimension of a plastic component used in digital camera. Currently the injection moulding machine process setting caused variations in the diameter exceeding the specification limit. Therefore the experiment is needed to identify the process factors that could be set to maintain the horizontal length dimension closest to the target value and smallest possible variation. The experimental model is used to investigate four factors to identify the factors having large effect by using the Full Factorial Design of Experiment (DOE). The experiment has emphasized the use of these designs in identifying the subset of factors that are active and provide some information about the interaction.

Abstract: The Hybrid Cellular Automata (HCA) algorithm has been used by several researchers to optimise structures during the last decade. Close observation of their work shows that the proposed optimisation algorithms are sensitive to the controller (local rule), the design variable and the field variable used. The aim of this work is to identify and understand the important parameters when using the HCA algorithm to optimise structures. For static loading, it is shown that the most important parameters are the design variable, the constraints on the design variable, the local rule, and the mesh density of the structure. The choice of the design variable affects the selection of the target value and the homogeneity of the resulting optimum structure. With constraints on the design variable, it is shown that the algorithm cannot always drive the structure to an optimum solution, as stresses in the resulting structure can be significantly higher than expected. Besides, the choice of the local rule and the mesh density of the structure can affect the convergence rate and may cause the algorithm to arrive at a local optimum rather than the global optimum solution.