The nature of statistical learning theory
The nature of statistical learning theory
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Back-Propagation: Theory, Architecture, and Applications
Back-Propagation: Theory, Architecture, and Applications
Using multiple adaptive regression splines to support decision making in code inspections
Journal of Systems and Software - Special issue: Applications of statistics in software engineering
Intrusion detection using an ensemble of intelligent paradigms
Journal of Network and Computer Applications - Special issue on computational intelligence on the internet
A hybrid sales forecasting system based on clustering and decision trees
Decision Support Systems
Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
Expert Systems with Applications: An International Journal
Predicting object-oriented software maintainability using multivariate adaptive regression splines
Journal of Systems and Software
A neural clustering and classification system for sales forecasting of new apparel items
Applied Soft Computing
Software reliability prediction by soft computing techniques
Journal of Systems and Software
Sales forecasting using extreme learning machine with applications in fashion retailing
Decision Support Systems
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions
Expert Systems with Applications: An International Journal
The forecasting model based on wavelet ν-support vector machine
Expert Systems with Applications: An International Journal
Mining the customer credit using hybrid support vector machine technique
Expert Systems with Applications: An International Journal
Financial time series forecasting using independent component analysis and support vector regression
Decision Support Systems
Expert Systems with Applications: An International Journal
ACIIDS '09 Proceedings of the 2009 First Asian Conference on Intelligent Information and Database Systems
Computational Statistics & Data Analysis
Expert Systems with Applications: An International Journal
Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry
Expert Systems with Applications: An International Journal
A sales forecasting model for new-released and nonlinear sales trend products
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A two-stage dynamic sales forecasting model for the fashion retail
Expert Systems with Applications: An International Journal
An intelligent fast sales forecasting model for fashion products
Expert Systems with Applications: An International Journal
IEEE Transactions on Information Theory
Support vector machine with adaptive parameters in financial time series forecasting
IEEE Transactions on Neural Networks
Learning convergence in the cerebellar model articulation controller
IEEE Transactions on Neural Networks
RCMAC Hybrid Control for MIMO Uncertain Nonlinear Systems Using Sliding-Mode Technology
IEEE Transactions on Neural Networks
Engineering Applications of Artificial Intelligence
Hi-index | 0.00 |
Artificial neural networks (ANNs) have been found to be useful for sales/demand forecasting. However, one of the main shortcomings of ANNs is their inability to identify important forecasting variables. This study uses multivariate adaptive regression splines (MARS), a nonlinear and non-parametric regression methodology, to construct sales forecasting models for computer wholesalers. Through the outstanding variable screening ability of MARS, important sales forecasting variables for computer wholesalers can be obtained to enable them to make better sales management decisions. Two sets of real sales data collected from Taiwanese computer wholesalers are used to evaluate the performance of MARS. The experimental results show that the MARS model outperforms backpropagation neural networks, a support vector machine, a cerebellar model articulation controller neural network, an extreme learning machine, an ARIMA model, a multivariate linear regression model, and four two-stage forecasting schemes across various performance criteria. Moreover, the MARS forecasting results provide useful information about the relationships between the forecasting variables selected and sales amounts through the basis functions, important predictor variables, and the MARS prediction function obtained, and hence they have important implications for the implementation of appropriate sales decisions or strategies.