S. Mukhopadhyay

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Lumpy demand forecasting using neural networks

A. Solis, R. Gutierrez, S. Mukhopadhyay, 2001, PICMET '01. Portland International Conference on Management of Engineering and Technology. Proceedings Vol.1: Book of Summaries (IEEE Cat. No.01CH37199).

THE DETERMINANTS OF QUALITY OF SOFTWARE DEVELOPMENT PROJECTS

S. Mukhopadhyay, 2013 .

Border Region Bridge and Air Transport Predictability

S. Mukhopadhyay, T. Fullerton, 2013 .

International market selection and subsidiary performance : A neural network approach

Timothy J. Wilkinson, Somnath Mukhopadhyay, Keith D. Brouthers, 2009 .

A New Approach for Optimizing Initial Parameters of Lorenz Attractor and Its Application in PRNG

S. Mukhopadhyay, Ramen Pal, 2020 .

Intermittent demand forecasting and stock control: An empirical study

A. Solis, S. Mukhopadhyay, L. Nicoletti, 2013 .

A polynomial time algorithm for generating neural networks for classification problems

A. Roy, S. Mukhopadhyay, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Different Length Genetic Algorithm-Based Clustering of Indian Stocks for Portfolio Optimization

S. Mukhopadhyay, T. Chaudhuri, 2019 .

Approximate and exact corrections of the bias in Croston?s method when forecasting lumpy demand: empirical evaluation

A. Solis, S. Mukhopadhyay, F. Longo, 2014 .

Global growth of service innovation : influence of national culture and organizational structure

S. Mukhopadhyay, 2022 .

Effects of ethnicity and gender on ethically driven small business performance

S. Mukhopadhyay, G. Frankwick, Denisse Olivas, 2022, Journal of Small Business and Enterprise Development.

Does Social Communicability Mediate the Role of Trust in Mobile Phone Adoption? An Individual Level Multi-nation Exploratory Study

K. Bagchi, S. Mukhopadhyay, 2012, ICIS 2012.

Factors influencing business intelligence-enabled success in global companies: an empirical study

K. Bagchi, L. Gemoets, S. Mukhopadhyay, 2019, Int. J. Bus. Inf. Syst..

Handbook of Research on Natural Computing for Optimization Problems

J. K. Mandal, Tandra Pal, Somnath Mukhopadhyay, 2016 .

Scheduling workers: A multi-criteria model considering their satisfaction

Giuseppe Paletta, José Humberto Ablanedo-Rosas, Somnath Mukhopadhyay, 2019, Comput. Ind. Eng..

Portfolio formation and optimization with continuous realignment: A suggested method for choosing the best portfolio of stocks using variable length NSGA-II

Somnath Mukhopadhyay, Tamal Datta Chaudhuri, Ramen Pal, 2021, Expert systems with applications.

A Guided Problem-Based Learning (PBL) Approach: Impact on Critical Thinking

Subhashish Samaddar, Satish Nargundkar, Somnath Mukhopadhyay, 2014 .

Qutrit-Based Genetic Algorithm for Hyperspectral Image Thresholding

Siddhartha Bhattacharyya, Somnath Mukhopadhyay, Sandip Dey, 2021 .

Forecasting Irregular and Lumpy Demands: Combining Alternative Approaches

Adriano O. Solis, Somnath Mukhopadhyay, Rafael S. Gutierrez, 2013 .

Estimation, suppression and optimization of impulses in digital imagery

Somnath Mukhopadhyay, S. Mukhopadhyay, 2014 .

Brain-like Supervised Learning in Pattern Classification Using Linear Programming: An Overview and Practical Research Prospects

Somnath Mukhopadhyay, Asim Roy, A. Roy, 2013 .

Disease Detection Analytics: A Simple Linear Convex Programming Algorithm for Breast Cancer and Diabetes Incidence Decisions

Adriano O. Solis, Subhashish Samaddar, Somnath Mukhopadhyay, 2018, Decis. Sci..

An empirical investigation of comparative performance of approximate and exact corrections of the bias in Croston's method in forecasting lumpy demand

Adriano O. Solis, Francesco Longo, Letizia Nicoletti, 2017, Int. J. Simul. Process. Model..

Editor’s note: artificial reasoning inspired intelligent systems

Somnath Mukhopadhyay, S. Mukhopadhyay, 2021, Innovations in Systems and Software Engineering.

Lumpy demand characterization and forecasting performance using neural networks

Adriano O. Solis, Somnath Mukhopadhyay, Rafael S. Gutierrez, 2008 .

Factors influencing business intelligence-enabled success in global companies: an empirical study

Leopoldo A. Gemoets, Somnath Mukhopadhyay, Kallol Kumar Bagchi, 2019, Int. J. Bus. Inf. Syst..

Traditional operational research and biologically motivated optimization models to predict multi-national Internet adoptions

Somnath Mukhopadhyay, Kallol Bagchi, K. Bagchi, 2013 .

Tea leaf disease detection using multi-objective image segmentation

Debashis De, Somnath Mukhopadhyay, Ramen Pal, 2020, Multimedia Tools and Applications.

A polynomial time algorithm for the construction and training of a class of multilayer perceptrons

Somnath Mukhopadhyay, Asim Roy, Lark Sang Kim, 1993, Neural Networks.

Variable Length PSO-Based Image Clustering for Image Denoising

J. K. Mandal, Tandra Pal, Somnath Mukhopadhyay, 2016 .

A Polynomial Time Algorithm for Generating Neural Networks for Pattern Classification: Its Stability Properties and Some Test Results

Somnath Mukhopadhyay, Asim Roy, Sandeep Govil, 1993, Neural Computation.

Methods for pattern selection, class-specific feature selection and classification for automated learning.

Somnath Mukhopadhyay, Asim Roy, Patrick D. Mackin, 2013, Neural networks : the official journal of the International Neural Network Society.

Modelling mobile technology growth using diffusion models and Neural Networks

Somnath Mukhopadhyay, Kallol Kumar Bagchi, Godwin J. Udo, 2009, Int. J. Electron. Bus..

Improving Revenue Management Decision Making for Airlines by Evaluating Analyst-Adjusted Passenger Demand Forecasts

Subhashish Samaddar, Somnath Mukhopadhyay, Glenn Colville, 2007, Decis. Sci..

Measuring Internet-Commerce Success: What Factors are Important?

Somnath Mukhopadhyay, Jimmie L. Joseph, M. Adam Mahmood, 2008 .

Inventory control performance of various forecasting methods when demand is lumpy

Adriano O. Solis, Somnath Mukhopadhyay, Rafael S. Gutierrez, 2010 .

Consumer purchasing behaviour and e-commerce adoption factors

Mo Adam Mahmood, Somnath Mukhopadhyay, Jimmie L. Joseph, 2009, Int. J. Electron. Bus..

Very high-resolution satellite image segmentation using variable-length multi-objective genetic clustering for multi-class change detection

P. Suganthan, S. Mukhopadhyay, D. Chakraborty, 2022, J. King Saud Univ. Comput. Inf. Sci..

Empirical Study of Propositionalization Approaches

S. Mukhopadhyay, Tanika Chakraborty, Kartick Chandra Mondal, 2021, Advances in Intelligent Systems and Computing.

A Novel Directional Weighted Minimum Deviation (DWMD) Based Filter for Removal of Random Valued Impulse Noise pdf

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2012, ArXiv.

Image denoising based on sub-image restoration through threshold optimisation

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2015, Int. J. Comput. Intell. Stud..

A Fuzzy Switching Median Filter of Impulses in Digital Imagery (FSMF)

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2014, Circuits Syst. Signal Process..

Denoising of digital images through PSO based pixel classification

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2013, Central European Journal of Computer Science.

Algorithms for Denoising Medical and Digital Images

J. K. Mandal, S. Mukhopadhyay, 2014 .

Adaptive Median Filtering Based on Unsupervised Classification of Pixels

J. K. Mandal, Somnath Mukhopadhyay, Jyotsna Kumar Mandal, 2013 .

Iterative generation of higher-order nets in polynomial time using linear programming

Somnath Mukhopadhyay, Asim Roy, A. Roy, 1997, IEEE Trans. Neural Networks.

Computational Intelligence, Communications, and Business Analytics

J. K. Mandal, Paramartha Dutta, Somnath Mukhopadhyay, 2017, Communications in Computer and Information Science.

Methodologies and Application Issues of Contemporary Computing Framework

J. K. Mandal, S. Mukhopadhyay, P. Dutta, 2018, Springer Singapore.

The Accuracy of Non‐traditional versus Traditional Methods of Forecasting Lumpy Demand

Adriano O. Solis, Somnath Mukhopadhyay, Rafael S. Gutierrez, 2012 .

A Hybrid PSO-Fuzzy Based Algorithm for Clustering Indian Stock Market Data

J. K. Mandal, Somnath Mukhopadhyay, Jyotsna Kumar Mandal, 2017, CICBA.

GA Based Denoising of Impulses (GADI)

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2011, CISIM.

Image Clustering Based on Different Length Particle Swarm Optimization (DPSO)

J. K. Mandal, Tandra Pal, Somnath Mukhopadhyay, 2014, FICTA.

Lumpy demand forecasting using neural networks

R. Quintana, L. F. Luna, R. Gutierrez, 2001, PICMET '01. Portland International Conference on Management of Engineering and Technology. Proceedings Vol.1: Book of Summaries (IEEE Cat. No.01CH37199).

Global Diffusion of the Internet IX: Predicting Global Diffusion of the Internet: An Alternative to Diffusion Models

Somnath Mukhopadhyay, S. Mukhopadhyay, 2006, Commun. Assoc. Inf. Syst..

Wavelet based Denoising of Medical Images Using Sub-band Adaptive Thresholding through Genetic Algorithm

J. K. Mandal, Somnath Mukhopadhyay, S. Mukhopadhyay, 2013 .

Original Contribution: A polynomial time algorithm for the construction and training of a class of multilayer perceptrons

A. Roy, S. Mukhopadhyay, Lark-Sang Kim, 1993 .

Computational Intelligence, Communications, and Business Analytics

Xiaokang Yang, J. K. Mandal, Dominik Ślęzak, 2017, Communications in Computer and Information Science.

A Hybrid Model for Optimal Pseudorandom Bit Sequence Generation

Somnath Mukhopadhyay, Ramen Pal, S. Mukhopadhyay, 2018, CICBA.