G. Weckman

发表

Assessing dependability of wireless networks using neural networks

A. Snow, P. Rastogi, G. Weckman, 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

A review of demand forecasting models and methodological developments within tourism and passenger transportation industry

William A. Young, G. Weckman, Iman Ghalehkhondabi, 2019, Journal of Tourism Futures.

A robust optimisation model for production planning and pricing under demand uncertainty

William A. Young, G. Weckman, Ehsan Ardjmand, 2016 .

Use of Artificial Neural Networks for Predicting Crude Oil Effect on CO2 Corrosion of Carbon Steels

G. Weckman, S. Nešić, Sandra Hernandez, 2005 .

Use of Artificial Neural Networks for Predicting Crude Oil Effect on Carbon Dioxide Corrosion of Carbon Steels

Vishal V. Ghai, G. Weckman, S. Nešić, 2006 .

An Integrated Stock Market Forecasting Model Using Neural Networks

Gary R. Weckman, Jon H. Marvel, Andrew P. Snow, 2008 .

An overview of energy demand forecasting methods published in 2005–2015

Gary R. Weckman, Ehsan Ardjmand, Iman Ghalehkhondabi, 2017 .

A critical appraisal of epidemiological studies investigating the effects of ultrafine particles on human health

R. Shell, G. Weckman, A. Genaidy, 2008 .

Neural net modeling of estuarine indicators: Hindcasting phytoplankton biomass and net ecosystem production in the Neuse (North Carolina) and Trout (Florida) Rivers, USA

Gary R. Weckman, Hans W. Paerl, David F. Millie, 2006 .

Learning before Erring: A Brief Note on the Influence of Dielectric Materials to pursue Moore’s Law

William A. Young, G. Weckman, S. Kaya, 2009 .

Determining Hall of Fame Status for Major League Baseball Using an Artificial Neural Network

William A. Young, G. Weckman, W. Holland, 2008 .

An Approach to Analyzing the Retirement Satisfaction among Men and Women Based on Artificial Neural Networks and Decision Trees

A. Snow, G. Weckman, Ehsan Ardjmand, 2017 .

Using Neural Networks to Predict Rainfall Patterns in South Texas

G. Weckman, R. Mclauchlan, J. Hernandez, 2000 .

A critical appraisal of epidemiological studies investigating the effects of ultrafine particles on human health

R. Shell, G. Weckman, A. Genaidy, 2008 .

Analyzing the Retirement Satisfaction Predictors among Men and Women Using a MultiLayer Feed Forward Neural Network and Decision Trees

A. Snow, G. Weckman, Ehsan Ardjmand, 2016 .

Health effects of nanomaterials: A critical appraisal approach and research to practice

R. Shell, G. Weckman, A. Genaidy, 2008 .

Applying a hybrid artificial immune systems to the job shop scheduling problem

William A. Young, Akshata A. Bondal, Magda M. Rinder, 2012, Neural Computing and Applications.

An overview of energy demand forecasting methods published in 2005–2015

William A. Young, G. Weckman, Iman Ghalehkhondabi, 2016, Energy Systems.

Decision making model to predict presence of coronary artery disease using neural network and C5.0 decision tree

Dale T. Masel, G. Weckman, Ehsan Ahmadi, 2017, Journal of Ambient Intelligence and Humanized Computing.

Water demand forecasting: review of soft computing methods

Ehsan Ardjmand, Iman Ghalehkhondabi, William A Young, 2017, Environmental Monitoring and Assessment.

A State-Based Sensitivity Analysis for Distinguishing the Global Importance of Predictor Variables in Artificial Neural Networks

Gary R. Weckman, Ehsan Ardjmand, William A. Young, 2016, Adv. Artif. Neural Syst..

Training the feedforward neural network using unconscious search

Gary R. Weckman, Ehsan Ardjmand, Mohammad Reza Amin-Naseri, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Applying genetic algorithm to a new bi-objective stochastic model for transportation, location, and allocation of hazardous materials

Gary R. Weckman, Ehsan Ardjmand, Namkyu Park, 2016, Expert Syst. Appl..

An investigation of TREPAN utilising a continuous oracle model

Gary R. Weckman, William A. Young, Maimuna H. Rangwala, 2011, Int. J. Data Anal. Tech. Strateg..

Artificial Neural Networks and Their Applications in Business

William A. Young, Gary R. Weckman, Trevor J. Bihl, 2019, Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction.

Applying genetic algorithm to a new location and routing model of hazardous materials

Gary R. Weckman, Manjeet Singh, Ehsan Ardjmand, 2015 .

Integrated decision making model for pricing and locating the customer order decoupling point of a newsvendor supply chain

Gary R. Weckman, Ehsan Ardjmand, Iman Ghalehkhondabi, 2017 .

Integrated decision making model for pricing and locating the customer order decoupling point of a newsvendor supply chain

G. Weckman, Iman Ghalehkhondabi, Ehsan Ardjmand, 2016, OPSEARCH.

Application of decision support systems in scheduling/planning of manufacturing/service systems: a critical review

William A. Young, Gary R. Weckman, Ehsan Ardjmand, 2016 .

Using artificial intelligence for CyanoHAB niche modeling: discovery and visualization of Microcystis–environmental associations within western Lake Erie

Gary R. Weckman, Ehsan Ardjmand, Robert A. Shuchman, 2014 .

A survey of methodologies for the treatment of missing values within datasets: limitations and benefits

William A. Young, Gary R. Weckman, William A. Young, 2011 .

Financial Asset Management Using Artificial Neural Networks

Gary R. Weckman, William A. Young, Azadeh Sadeghi, 2020, Int. J. Oper. Res. Inf. Syst..

The discrete Unconscious search and its application to uncapacitated facility location problem

Gary R. Weckman, Ehsan Ardjmand, Namkyu Park, 2014, Comput. Ind. Eng..

Modeling microalgal abundance with artificial neural networks: Demonstration of a heuristic 'Grey-Box' to deconvolve and quantify environmental influences

Gary R. Weckman, William A. Young, Hunter J. Carrick, 2012, Environ. Model. Softw..

A multi-objective two-echelon location-routing problem for cash logistics: A metaheuristic approach

Gary R. Weckman, Ehsan Ardjmand, William A. Young, 2021, Appl. Soft Comput..

A hybrid artificial neural network, genetic algorithm and column generation heuristic for minimizing makespan in manual order picking operations

Gary R. Weckman, Ehsan Ardjmand, Heman Shakeri, 2020, Expert Syst. Appl..

A neural network job-shop scheduler

Gary R. Weckman, David A. Koonce, Chandrasekhar V. Ganduri, 2008, J. Intell. Manuf..

Meeting SLA Availability Guarantees through Engineering Margin

Gary R. Weckman, Andrew P. Snow, Vivek Gupta, 2010, 2010 Ninth International Conference on Networks.

Decision making model to predict presence of coronary artery disease using neural network and C5.0 decision tree

Gary R. Weckman, Ehsan Ahmadi, Dale T. Masel, 2017, Journal of Ambient Intelligence and Humanized Computing.

MODELING PHYTOPLANKTON ABUNDANCE IN SAGINAW BAY, LAKE HURON: USING ARTIFICIAL NEURAL NETWORKS TO DISCERN FUNCTIONAL INFLUENCE OF ENVIRONMENTAL VARIABLES AND RELEVANCE TO A GREAT LAKES OBSERVING SYSTEM 1

G. Weckman, D. Millie, G. Fahnenstiel, 2006 .

Rubrics on the Fly: Improving Efficiency and Consistency with a Rapid Grading and Feedback System

William A. Young, Gary R. Weckman, William A. Young, 2015 .

Multiple customer order decoupling points within a hybrid MTS/MTO manufacturing supply chain with uncertain demands in two consecutive echelons

Gary R. Weckman, Dusan Sormaz, Iman Ghalehkhondabi, 2016 .

Multiple customer order decoupling points within a hybrid MTS/MTO manufacturing supply chain with uncertain demands in two consecutive echelons

G. Weckman, D. Sormaz, Iman Ghalehkhondabi, 2016, OPSEARCH.

A Prescriptive Stock Market Investment Strategy for the Restaurant Industry using an Artificial Neural Network Methodology

Gary R. Weckman, Ehsan Ardjmand, Andrew P. Snow, 2020, Deep Learning and Neural Networks.

Decision support approach to fleet maintenance requirements in the aviation industry

Gary R. Weckman, Jon H. Marvel, Richard Shell, 2006 .

Selective ensemble based on extreme learning machine and improved discrete artificial fish swarm algorithm for haze forecast

G. Weckman, Zhiwei Ni, Feifei Jin, 2018, Applied Intelligence.

The nano enterprise: A survey of health and safety concerns, considerations, and proposed improvement strategies to reduce potential adverse effects

Waldemar Karwowski, Gary R. Weckman, Ash Genaidy, 2006 .

Coastal ‘Big Data’ and nature-inspired computation: Prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric

Gary R. Weckman, Ehsan Ardjmand, William A. Young, 2013 .

AN “ENVIRO‐INFORMATIC” ASSESSMENT OF SAGINAW BAY (LAKE HURON, USA) PHYTOPLANKTON: DATA‐DRIVEN CHARACTERIZATION AND MODELING OF MICROCYSTIS (CYANOPHYTA) 1

Gary R Weckman, G. Weckman, D. Millie, 2011, Journal of phycology.

Using artificial neural networks to enhance CART

William A. Young, A. Snow, G. Weckman, 2012, Neural Computing and Applications.

A critical appraisal of epidemiological studies investigating the effects of ultrafine particles on human health

R. Shell, G. Weckman, A. Genaidy, 2008 .

Defining, Understanding, and Addressing Big Data

William A. Young, Gary R. Weckman, Trevor J. Bihl, 2016 .

Using a heuristic approach to derive a grey-box model through an artificial neural network knowledge extraction technique

Gary R. Weckman, William A. Young, G. Weckman, 2010, Neural Computing and Applications.

Artificial Neural Networks for Business Analytics

William A. Young, Gary R. Weckman, Trevor J. Bihl, 2014 .

Forecasting ATM Cash Demand Before and During the COVID-19 Pandemic Using an Extensive Evaluation of Statistical and Machine Learning Models

G. Weckman, M. Aghaaminiha, Alireza Fallahtafti, 2022, SN Computer Science.

Knowledge Extraction from the Neural ‘Black Box’ in Ecological Monitoring

Gary R. Weckman, William A. Young, David F. Millie, 2009 .

Selective ensemble based on extreme learning machine and improved discrete artificial fish swarm algorithm for haze forecast

Gary R. Weckman, Zhiwei Ni, Xuhui Zhu, 2017, Applied Intelligence.

Using Voronoi diagrams to improve classification performances when modeling imbalanced datasets

William A. Young, G. Weckman, D. Chelberg, 2015, Neural Computing and Applications.

Healthcare Scheduling by Data Mining: Literature Review and Future Directions

Gary R. Weckman, Namkyu Park, William A. Young, 2012 .

Category: Decision Support Decision Support Systems in Business Perspective of Chapter

G. Weckman, 2016 .

EXTRACTING KNOWLEDGE FROM CARBON DIOXIDE CORROSION INHIBITION WITH ARTIFICIAL NEURAL NETWORKS

Gary R. Weckman, William A. Young, Maimuna H. Rangwala, 2010 .

Trepan-Plus: An Extension of a Decision Tree Extraction Algorithm Utilizing Artificial Neural Networks

Gary R. Weckman, Jon H. Marvel, William A. Young, 2007 .

Factors affecting healthcare costs in manufacturing

Waldemar Karwowski, Ash Genaidy, Richard Shell, 2008 .

An Intelligent Model to Predict Energy Performances of Residential Buildings Based on Deep Neural Networks

Gary R. Weckman, William A. Young, Azadeh Sadeghi, 2020, Energies.