An improved approach based on fuzzy clustering and Back-Propagation Neural Networks with adaptive learning rate for sales forecasting: Case study of PCB industry
This paper describes new hybrid sales forecasting system based on fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learning rate (FCBPN).The proposed approach is composed of three stages: (1) Winters Exponential Smoothing method will be utilized to take the trend effect into consideration; (2) utilizing Fuzzy C-Means clustering method (Used in an clusters memberships fuzzy system (CMFS)), the clusters membership levels of each normalized data records will be extracted; (3) Each cluster will be fed into parallel BP networks with a learning rate adapted as the level of cluster membership of training data records. Compared to many researches which use Hard clustering, we employ fuzzy clustering which permits each data record to belong to each cluster to a certain degree, which allows the clusters to be larger which consequently increases the accuracy of the proposed forecasting system . Printed Circuit Board (PCB) will be used as a case study to evaluate the precision of our proposed architecture. Experimental results show that the proposed model outperforms the previous and traditional approaches. Therefore, it is a very promising solution for industrial forecasting.
Keywords: Sales forecasting, fuzzy clustering, fuzzy system, Printed circuit boards, back propagation network, Hybrid intelligence approach.
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ABOUT THE AUTHORS
Attariuas Hicham
received the computer engineer degree in 2009 from ENSAIS national school of computer science and systems analysis in Rabat, Morocco. Currently, he is a PhD Student in Computer Science. Current research interests: fuzzy system, intelligence system, bac-propagation network, genetic intelligent system.
Bouhorma Mohamed
received the the PhD degree in Telecommunications and Computer Engineering. He is a Professor of Telecommunications and Computer Engineering in Abdelmalek Essaadi University. He has been a member of the Organizing and the Scientific Committees of several symposia and conferences dealing with Intelligent system, Mobile Networks, Telecommunications technologies.
El Fallahi Abdellah
received the the PhD degree in neural systems in 2008 from Valencia University, Spain. He is Professor in the logistics and transport department at the National School of applied sciences.His teaching is devoted to the logistics and transport, Integer and Linear Programming in Mathematics and heuristics .His research interest focuses on the development of meta-heuristics for hard optimization problems.
Attariuas Hicham
received the computer engineer degree in 2009 from ENSAIS national school of computer science and systems analysis in Rabat, Morocco. Currently, he is a PhD Student in Computer Science. Current research interests: fuzzy system, intelligence system, bac-propagation network, genetic intelligent system.
Bouhorma Mohamed
received the the PhD degree in Telecommunications and Computer Engineering. He is a Professor of Telecommunications and Computer Engineering in Abdelmalek Essaadi University. He has been a member of the Organizing and the Scientific Committees of several symposia and conferences dealing with Intelligent system, Mobile Networks, Telecommunications technologies.
El Fallahi Abdellah
received the the PhD degree in neural systems in 2008 from Valencia University, Spain. He is Professor in the logistics and transport department at the National School of applied sciences.His teaching is devoted to the logistics and transport, Integer and Linear Programming in Mathematics and heuristics .His research interest focuses on the development of meta-heuristics for hard optimization problems.
