Communications of the ACM
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Data mining techniques for optimizing inventories for electronic commerce
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Demand forecast in a supermarket using a hybrid intelligent system
Design and application of hybrid intelligent systems
Knowledge Discovery from Transportation Network Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
A New Insight Into Prediction Modeling Systems
Journal of Integrated Design & Process Science
A Sequential Hybrid Forecasting System for Demand Prediction
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
The criticality of spare parts evaluating model using artificial neural network approach
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
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An increasing number of organizations are involved inthe development of information systems for effective linkageswith their suppliers, customers, and other channel partnersinvolved in transportation, distribution, warehousing andmaintenance activities. We use neural networkbased data mining and knowledge discovery techniques to solvethe problems of inventory in a large medical distributioncompany. The paper describes the use oftraditional statistical techniques to evaluate the best neuralnetwork type. Based on the neural network model describedin this paper, a prototype was conceived with data from a largedecentralized organization. The prototype was successful inreducing the total level of inventory by 50% in theorganization, while maintaining the same level of probabilitythat a particular customer‘s demand will be satisfied.