An intelligent decision support system for forecasting and optimization of complex personnel attributes in a large bank

Authors:
Ali Azadeh;Morteza Saberi;Zahra Jiryaei
Affiliations:
Department of Industrial Engineering, College of Engineering, University of Tehran, P.O. Box 11365-4563, Iran;Institute for Digital Ecosystems & Business Intelligence, Curtin University of Technology, Perth, Australia;Department of Industrial Engineering, College of Engineering, University of Tehran, P.O. Box 11365-4563, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 14
Cited 0

Original Contribution: A scaled conjugate gradient algorithm for fast supervised learning

Neural Networks
Variable precision rough set model

Journal of Computer and System Sciences
Operations, Quality, and Profitability in the Provision of Banking Services

Management Science - Special issue on the performance of financial Institutions
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Data Envelopment Analysis: Theory, Methodology, and Application

Data Envelopment Analysis: Theory, Methodology, and Application
Feature extraction using rough set theory and genetic algorithms--an application for the simplification of product quality evaluation

Computers and Industrial Engineering
Knowledge discovery techniques for predicting country investment risk

Computers and Industrial Engineering
Extraction of Experts' Decision Process from Clinical Databases Using Rough Set Model

PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Modelling Customer Retention with Rough Data Models

PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Fuzzy rough sets hybrid scheme for breast cancer detection

Image and Vision Computing
Extracting drug utilization knowledge using self-organizing map and rough set theory

Expert Systems with Applications: An International Journal
Reduction method based on a new fuzzy rough set in fuzzy information system and its applications to scheduling problems

Computers & Mathematics with Applications
An integrated Data Envelopment Analysis-Artificial Neural Network-Rough Set Algorithm for assessment of personnel efficiency

Expert Systems with Applications: An International Journal
Autonomous decision-making: a data mining approach

IEEE Transactions on Information Technology in Biomedicine

Quantified Score

Hi-index	12.05

Visualization

Abstract

Developing decision support system (DSS) can overcome the issues with personnel attributes and specifications. Personnel specifications have greatest impact on total efficiency. They can enhance total efficiency of critical personnel attributes. This study presents an intelligent integrated decision support system (DSS) for forecasting and optimization of complex personnel efficiency. DSS assesses the impact of personnel efficiency by data envelopment analysis (DEA), artificial neural network (ANN), rough set theory (RST), and K-Means clustering algorithm. DEA has two roles in this study. It provides data to ANN and finally it selects the best reduct through ANN results. Reduct is described as a minimum subset of features, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is used for forecasting total efficiency. Finally, K-Means algorithm is used to develop the DSS. A procedure is proposed to develop the DSS with stated tools and completed rule base. The DSS could help managers to forecast and optimize efficiencies by selected attributes and grouping inferred efficiency. Also, it is an ideal tool for careful forecasting and planning. The proposed DSS is applied to an actual banking system and its superiorities and advantages are discussed.