Forecasting of Retail Sales Data Using Differential Evolution

被引：0

作者：

Majhi, Ritanjali ^{[1
]}

Panda, Ganapati ^{[3
]}

Majhi, Babita ^{[2
]}

Panigrahi, S. K. ^{[4
]}

Mishra, Manoj Ku. ^{[2
]}

机构：

[1] Natl Inst Technol, Sch Management, Warangal, Andhra Pradesh, India

[2] Sikha O Anusandhan Deemed Univ, Inst Tech Educ & Res, Dept Informat Technol, Bhubaneswar, Orissa, India

[3] Indian Inst Technol Bhubaneswar, Sch Elect Sci, Bhubaneswar, Orissa, India

[4] Padmashree Kutartha Acharya Coll Engn, Dept Management Sci & Humanit, Baragarh, India

来源：

2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009) | 2009年

关键词：

Sales forecasting; differntial evolution; adaptive linear combiner; EFFICIENT PREDICTION; NEURAL-NETWORKS; MODELS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper aims to develop an efficient forecasting model using differential evolution (DE) based learning rule. The structure chosen is an adaptive linear combiner whose weights are trained using DE. The prediction performance of the resulting model is evaluated by feeding features of retail sales data for different months' ahead prediction. These results are compared with those obtained by GA based approach. The comparison demonstrates improved prediction of sales data by the proposed DE method.

引用

页码：1342 / +

页数：2

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