Neural Networks with Weight Function and Application

被引：0

作者：

Zhang Niaona ^{[1
]}

Lu Xiuhe ^{[1
]}

Zhang Dejiang ^{[1
]}

Chen Fang ^{[1
]}

机构：

[1] Changchun Univ Technol, Coll Elect & Elect Engn, Changchun, Peoples R China

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS ( ICAL 2009), VOLS 1-3 | 2009年

关键词：

neural networks; energy consumption forecasting; weight function; LEARNING ALGORITHM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Against these disadvantages like local minimum, slow convergence speed, non-convergence and difficulty in obtaining of global optimal point, the new Neural Networks with Weight Function is proposed in this paper with simple network topology constituted by input layer and output layer only. This network is used in establishing the Energy Consumption Forecasting Model of DAGUSHAN Ore Dressing Plant. According to the production data in actual production process and the gap of these data, different interpolation functions are selected to be the weight functions. Simulation examples show the good performance of this method that little calculation work, with no local minimum and slow convergence problems. Model mentioned above has minor error and the better prediction effect is obtained.

引用

页码：1273 / 1277

页数：5

共 8 条

[1] GRADIENT DESCENT LEARNING ALGORITHM OVERVIEW - A GENERAL DYNAMICAL-SYSTEMS PERSPECTIVE
BALDI, P
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1995, 6 (01): : 182 - 195
[2] AN ACCELERATED LEARNING ALGORITHM FOR MULTILAYER PERCEPTRONS - OPTIMIZATION LAYER-BY-LAYER
ERGEZINGER, S
THOMSEN, E
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1995, 6 (01): : 31 - 42
[3] FU Y, 2007, J JILIN U SCI ED, V45, P24
[4] LIU Y, 2002, J JILIN U INFORM SCI, V25, P188
[5] WANG X, 2005, CALCULATION METHOD
[6] WU D, 2000, CHINAS MAN GANESE IN, V2, P24
[7] ZHANG D, 2006, NEW THEORY ALGORITHM
[8] [张代远 ZHANG Daiyuan], 2006, [系统工程与电子技术, Systems engineering & electronics], V28, P1434

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