A bibliography of neural network business applications research: 1988–September 1994

: The purpose of this research is to present a comprehensive bibliography of neural network application research in business. One hundred and twenty-seven neural network application papers and reports are identified through exhaustive literature searches. A classification of these articles by application area reveals that neural networks are being used for a diverse range of corporate functional activities, particularly in the areas of production/operations and finance. Information on the neural network development language/tool, the learning paradigm and the computer operating environment as reported in each article is included. Those journals which have published the most neural network business applications are also presented.

[1]  Katsumi Morikawa,et al.  Neural network approach for minimizing the makespan of the general job-shop , 1994 .

[2]  Tor Guimaraes,et al.  Integrating artificial neural networks with rule-based expert systems , 1994, Decis. Support Syst..

[3]  Suraj M. Alexander,et al.  The investigation of new approaches to business data analysis , 1993 .

[4]  L. Burke.  A neural design for solution of the maximal independent set problem , 1992 .

[5]  G. Allen Pugh.  A COMPARISON OF NEURAL NETWORKS TO SPC CHARTS , 1991 .

[6]  Noel E. Sharkey,et al.  Neural computing for software reliability , 1994 .

[7]  Hiromitsu Kumamoto,et al.  Failure diagnosis of a servovalve by neural networks with new learning algorithm and structure analysis , 1990 .

[8]  Norma Faris Hubele,et al.  Back-propagation pattern recognizers for X¯ control charts: methodology and performance , 1993 .

[9]  Marcus Brown,et al.  User Identification via Keystroke Characteristics of Typed Names using Neural Networks , 1993, Int. J. Man Mach. Stud..

[10]  Nallan C. Suresh,et al.  Performance of Fuzzy ART neural network for group technology cell formation , 1994 .

[11]  G. A. Pugh.  Synthetic neural networks for process control , 1989 .

[12]  N F Hubele,et al.  X¯ CONTROL CHART PATTERN IDENTIFICATION THROUGH EFFICIENT OFF-LINE NEURAL NETWORK TRAINING , 1993 .

[13]  Herbert Moskowitz,et al.  Integrating Neural Networks and Semi‐Markov Processes for Automated Knowledge Acquisition: An Application to Real‐time Scheduling* , 1992 .

[14]  Alice E. Smith,et al.  X-bar and R control chart interpretation using neural computing , 1994 .

[15]  E. Mine Cinar,et al.  Neural Networks: A New Tool for Predicting Thrift Failures , 1992 .

[16]  Amit Kumar Ray,et al.  Equipment fault diagnosis—A neural network approach , 1991 .

[17]  Kar Yan Tam,et al.  Neural network models and the prediction of bank bankruptcy , 1991 .

[18]  F. S. Wong,et al.  Fuzzy Neural Systems for Stock Selection , 1992 .

[19]  N. Suresh,et al.  Machine-component cell formation in group technology : a neural network approach , 1992 .

[20]  R. Proctor.  An Expert System to Aid in Staff Selection: A Neural Network Approach , 1991 .

[21]  Pi-Sheng Deng,et al.  Experimentation with a back-propagation neural network: An application to planning end user system development , 1993, Inf. Manag..

[22]  Sema E. Alptekin,et al.  Artificial neural networks for robotics coordinate transformation , 1992 .

[23]  Kenneth R. Currie.  An intelligent grouping algorithm for cellular manufacturing , 1992 .

[24]  David W. Wright,et al.  Using Artificial Neural Networks to Pick Stocks , 1993 .

[25]  Hsu-Pin Ben Wang,et al.  Classification of autoregressive spectral estimated signal patterns using an adaptive resonance theory neural network , 1993 .

[26]  Melody Y. Kiang,et al.  Predicting Bank Failures: A neural network approach , 1990, Appl. Artif. Intell..

[27]  Godwin J. Udo,et al.  Neural network performance on the bankruptcy classification problem , 1993 .

[28]  Cihan H. Dagli,et al.  Genetic neuro-scheduler for job shop scheduling , 1993 .

[29]  Timo Sorsa,et al.  Neural networks in process fault diagnosis , 1991, IEEE Trans. Syst. Man Cybern..

[30]  Harald Hruschka,et al.  Determining market response functions by neural network modeling: A comparison to econometric techniques , 1993 .

[31]  S. Chi,et al.  Generalized part family formation using neural network techniques , 1992 .

[32]  Stavros A. Zenios,et al.  Predicting Prepayment Rates for Mortgages Using the Cascade-Correlation Learning Algorithm , 1993 .

[33]  Deborah F. Cook,et al.  A predictive neural network modelling system for manufacturing process parameters , 1992 .

[34]  T. Warren Liao,et al.  An evaluation of ART1 neural models for GT part family and machine cell forming , 1993 .

[35]  C. L. Philip Chen,et al.  An integration of neural network and rule-based systems for design and planning of mechanical assemblies , 1993, IEEE Trans. Syst. Man Cybern..

[36]  Andrew Kusiak,et al.  Grouping parts with a neural network , 1994 .

[37]  Jay Lee,et al.  Analysis of machine degradation using a neural network based pattern discrimination model , 1993 .

[38]  R. A. Proctor.  Selecting an Appropriate Strategy: A Structured Creative Decision Support Method , 1992 .

[39]  Chao-Hsien Chu,et al.  Neural network system for forecasting method selection , 1994, Decis. Support Syst..

[40]  Alain Lelu,et al.  From data analysis to neural networks: new prospects for efficient browsing through databases , 1991, J. Inf. Sci..

[41]  Sanjoy Ghose,et al.  Comparing the predictive performance of a neural network model with some traditional market response models , 1994 .

[42]  Nallan C. Suresh,et al.  A neural network system for shape-based classification and coding of rotational parts , 1991 .

[43]  Xuening Chu,et al.  Product manufacturability control for concurrent engineering , 1994 .

[44]  Adedeji Badiru,et al.  An artificial neural network case study: prediction versus classification in a manufacturing application , 1993 .

[45]  Jean-Yves Potvin,et al.  Neural networks for automated vehicle dispatching , 1992, Comput. Oper. Res..

[46]  Chien-Nan Huang,et al.  Comparison of image processing algorithms and neural networks in machine vision inspection , 1992 .

[47]  S.S. Rangwala,et al.  Learning and optimization of machining operations using computing abilities of neural networks , 1989, IEEE Trans. Syst. Man Cybern..

[48]  George Chryssolouris,et al.  The use of neural networks in determining operational policies for manufacturing systems , 1991 .

[49]  Youngohc Yoon,et al.  A Comparison of Discriminant Analysis versus Artificial Neural Networks , 1993 .

[50]  Y. Moon,et al.  An unified group technology implementation using the backpropagation learning rule of neural networks , 1991 .

[51]  Pamela K. Coats,et al.  Recognizing Financial Distress Patterns Using a Neural Network Tool , 1993 .

[52]  Duane DeSieno,et al.  Trading Equity Index Futures With a Neural Network , 1992 .

[53]  Laura I. Burke,et al.  An unsupervised neural network approach to tool wear identification , 1993 .

[54]  P. Gu,et al.  Expert self-organizing neural network for the design of cellular manufacturing systems , 1994 .

[55]  William Remus,et al.  Neural network models for intelligent support of managerial decision making , 1994, Decis. Support Syst..

[56]  W. Robertson,et al.  A neural algorithm for document clustering , 1991, Inf. Process. Manag..

[57]  Ingoo Han,et al.  An empirical investigation of some data effects on the classification accuracy of probit, ID3, and neural networks* , 1992 .

[58]  Richard T. Redmond,et al.  Expert systems for bond rating: a comparative analysis of statistical, rule‐based and neural network systems , 1993 .

[59]  Michael J. Shaw,et al.  A classification approach using multi-layered neural networks , 1994, Decis. Support Syst..

[60]  Gregory R. Madey,et al.  Integration of neurocomputing and system simulation for modeling continuous improvement systems in manufacturing , 1992, J. Intell. Manuf..

[61]  Alice E. Smith,et al.  Controlling industrial processes through supervised, feedforward neural networks , 1991 .

[62]  T. T. Narendran,et al.  Neural network model for design retrieval in manufacturing systems , 1992 .

[63]  Edward I. Altman,et al.  Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) , 1994 .

[64]  Luis Rabelo,et al.  Artificial neural networks for flexible manufacturing systems scheduling , 1993 .

[65]  Alec Evans,et al.  AIRCRAFT NOISE AND RESIDENTIAL PROPERTY VALUES: AN ARTIFICIAL NEURAL NETWORK APPROACH. , 1994 .

[66]  Youngohc Yoon,et al.  Applying Artificial Neural Networks to Investment Analysis , 1992 .

[67]  Nallan C. Suresh,et al.  An improved neural network leader algorithm for part-machine grouping in group technology , 1993 .

[68]  Desmond Fletcher,et al.  Forecasting with neural networks: An application using bankruptcy data , 1993, Inf. Manag..

[69]  K. T. Yeo,et al.  An expert neural network system for dynamic job shop scheduling , 1994 .

[70]  Judith M. Collins,et al.  AN APPLICATION OF THE THEORY OF NEURAL COMPUTATION TO THE PREDICTION OF WORKPLACE BEHAVIOR: AN ILLUSTRATION AND ASSESSMENT OF NETWORK ANALYSIS , 1993 .

[71]  Pi-Sheng Deng,et al.  Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model* , 1993 .

[72]  Scott Hamilton,et al.  The journal communication system for MIS research , 1982, DATB.

[73]  Andreas Stafylopatis,et al.  Pictorial Information Retrieval Using the Random Neural Network , 1992, IEEE Trans. Software Eng..

[74]  Gerald M. Knapp,et al.  Machine fault classification: a neural network approach , 1992 .

[75]  Melody Y. Kiang,et al.  Managerial Applications of Neural Networks: The Case of Bank Failure Predictions , 1992 .

[76]  Yoshiyasu Takefuji,et al.  Neural networks in design and manufacturing , 1993 .

[77]  T. Warren Liao,et al.  Integration of a feature-based CAD system and an ART1 neural model for GT coding and part family forming , 1994 .

[78]  Mohammad S. Obaidat,et al.  A Multilayer Neural Network System for Computer Access Security , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[79]  Jiann-Liang Chen,et al.  A neural-net approach to economic power dispatch , 1993 .

[80]  Ramesh Sharda,et al.  Bankruptcy prediction using neural networks , 1994, Decis. Support Syst..

[81]  G. Grudnitski,et al.  Forecasting S&P and gold futures prices: An application of neural networks , 1993 .

[82]  James P. Ignizio,et al.  A stochastic neural network for resource constrained scheduling , 1992, Comput. Oper. Res..

[83]  Kang G. Shin,et al.  Intelligent Coordination of Multiple Systems with Neural Networks , 1991, 1991 American Control Conference.

[84]  Jun Wang,et al.  A neural network approach to multiple-objective cutting parameter optimization based on fuzzy preference information , 1993 .

[85]  Sooyoung Kim,et al.  Neural network applications for scheduling jobs on parallel machines , 1993 .

[86]  Young B. Moon,et al.  Establishment of a neurocomputing model for part family/machine group identification , 1992, J. Intell. Manuf..

[87]  Paul J. Werbos,et al.  Maximizing long-term gas industry profits in two minutes in Lotus using neural network methods , 1989, IEEE Trans. Syst. Man Cybern..

[88]  L. T. Fan,et al.  Artificial intelligence for waste minimization in the process industry , 1993 .

[89]  Yuehwern Yih,et al.  ROBOT SCHEDULING IN A CIRCUIT BOARD PRODUCTION LINE:A HYBRID OR/ANN APPROACH , 1993 .

[90]  Colin O. Benjamin,et al.  Classifying U.S. manufacturing plant locations using an artificial neural network , 1992 .

[91]  Leticia Villegas,et al.  A neural network tool for identifying text-editing goals , 1994, Int. J. Hum. Comput. Stud..

[92]  Herbert L. Jensen,et al.  Using Neural Networks for Credit Scoring , 1992 .

[93]  Mark L. Gillenson,et al.  Academic Issues in MIS: Journals and Books , 1991, MIS Q..

[94]  T. T. Narendran,et al.  Machine-cell formation through neural network models , 1994 .

[95]  Akio Yamamoto,et al.  Scheduling for minimizing total actual flow time by neural networks , 1992 .

[96]  Utpal Roy,et al.  Connectionist models for part-family classifications , 1993 .

[97]  Tomas Velasco,et al.  Back propagation artificial neural networks for the analysis of quality control charts , 1993 .

[98]  Lawrence C. Rose,et al.  European Diversification Opportunities in the 1990's , 1992 .

[99]  Robert J. Kauffman,et al.  Comparing the Modeling Performance of Regression and Neural Networks as Data Quality Varies: A Business Value Approach , 1993, J. Manag. Inf. Syst..

[100]  Cihan H. Dagli.  Artificial Neural Networks for Intelligent Manufacturing , 1994 .

[101]  Qiwen Wang,et al.  A neural network model for the wire bonding process , 1993, Comput. Oper. Res..

[102]  James V. Hansen,et al.  Artificial Intelligence and Generalized Qualitative‐Response Models: An Empirical Test on Two Audit Decision‐Making Domains , 1992 .

[103]  K. F. Reinschmidt.  Neural networks; Next step for simulation and control , 1991 .