To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure ...To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.展开更多
For an enterprise, what is important is to have the self-dependent innovation ability so that it can en- hance the core competence unceasingly and acquire sustainable competitive advantages. In this paper, the indi- c...For an enterprise, what is important is to have the self-dependent innovation ability so that it can en- hance the core competence unceasingly and acquire sustainable competitive advantages. In this paper, the indi- cator system of the self-dependent innovation ability of equipment manufacturing enterprises in Shaanxi province is constructed, in which includes 4 one-level indicators and 13 two-level indicators; and conducts empirical re- search by applying the multi-level fuzzy comprehensive evaluation method.展开更多
基金Supported by the Shanxi Natural Science Foundation under contract number 20041070 and Natural Science Foundation of north u-niversity of China .
文摘To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.
基金supported by Fund for Higher Education Research of Northwestern Polytechnical University under Grant No.2012GJY19
文摘For an enterprise, what is important is to have the self-dependent innovation ability so that it can en- hance the core competence unceasingly and acquire sustainable competitive advantages. In this paper, the indi- cator system of the self-dependent innovation ability of equipment manufacturing enterprises in Shaanxi province is constructed, in which includes 4 one-level indicators and 13 two-level indicators; and conducts empirical re- search by applying the multi-level fuzzy comprehensive evaluation method.
