Study On Comprehensive Evaluation Model Of The Competence Of The Staff Based On BP Artificial Nerve Network

Personnel competence evaluation is an important function of modern human resource management. In theory and practice of human resource management, personnel competence refers to the conditions and elements that affect the job performance of personnel. It is the base on which the individual can complete the job, form the job performance and develop further. By analyzing the ability of the personnel being evaluated, we can use personnel ability evaluation to offer scientific personnel allocation, aiding the companies selecting personnel objectively and effectively, fully developing the initiative and creativity of personnel, and finally offer reference information for personnel decisions. It is important for company human resource allocation, using, and training.Personnel competence evaluation is affected by various factors to some extent, so the outcome of evaluation is difficult to be expressed with a mathematical function; it is a multivariate, complex and nonlinear. Currently, the general fact is we usually get less objective and correct result by using the evaluation methods and techniques often adopted by researchers'home and abroad. So the spread of personnel competence evaluation in company human resource management is greatly limited.Since the 80s of last century, the high techniques multi-subject concept of artificial neural network has attracted the attention of many neuron-biologists, psychologists and other scientists in mathematics, engineers and entrepreneurs; they are interested in this concept and have conducted researches on it. As the reaches go on, this concept has been widely used in such areas as signal and image processing, speech recognition, virtual reality, control system design, system simulation, artificial intelligence, company crisis management and early-warning, data mining, system identification and synthetic evaluation, etc.As artificial neural network possesses such advantages as parallel data processing ,fault-tolerant ,self-adaptive and self-learning and nonlinear, This paper is aimed to analyze personnel ability structure systematically and construct the artificial neural network model, in hope to improve the evaluation process, decrease the possible outcome differences caused by subjectivity of evaluators and finally invent a objectively quantified standard for evaluating the personnel ability generally and concisely.In preparing this paper, I have read huge volumes of classics and papers, and my work could be summarized as follows: 1. Generally introduced the ordinary methods of personnel ability evaluation, processed and analyzed relative theories and algorithm of artificial neural network, improved the method of personnel ability evaluation based on analyzing personnel ability structure and traditional means for personnel ability evaluation.2. Analyzed the probability of artificial neural network; introduced the principles and methods by which improving the current personnel evaluation with artificial neural network; constructed the new evaluation model based on BP artificial neural network; with the help of this model, created the index system of personnel ability evaluation, and then proposed means to quantify such indexes, then the indexes can be used as ideal input for artificial neural network training.3. Mentioned the difficulties during the research and the disadvantages, proposed ideas to further improve the research as the reference for the follow up researchers on this subject.