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Integration of AI and OR techniques in constraint programming for combinatorial optimization problems : first international conference, CPAIOR 2004, Nice, France, April 20-22, 2004 : proceedings

International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems (1st : 2004 : Nice, France) Jean-Charles Regin; Michel Rueher

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2
Nash-Stackelberg equilibrium solutions for linear multidivisional multilevel programming problems.
Nash-Stackelberg equilibrium solutions for linear multidivisional multilevel programming problems.
Nash-Stackelberg equilibrium solutions for linear multidivisional multilevel programming problems.
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Nash-Stackelberg equilibrium solutions for linear multidivisional multilevel programming problems.

Mao-Hua. Yang State University of New York at Buffalo. 2005

Dissertation Abstracts International 65-12B.

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3
Developing an accurate forecasting model for temporal and spatial ambulance demand via artificial neural networks: A comparative study of existing forecasting techniques vs. an artificial neural network.
Developing an accurate forecasting model for temporal and spatial ambulance demand via artificial neural networks: A comparative study of existing forecasting techniques vs. an artificial neural network.
Developing an accurate forecasting model for temporal and spatial ambulance demand via artificial neural networks: A comparative study of existing forecasting techniques vs. an artificial neural network.
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Developing an accurate forecasting model for temporal and spatial ambulance demand via artificial neural networks: A comparative study of existing forecasting techniques vs. an artificial neural network.

Hubert Holland, III. Setzler The University of North Carolina at Charlotte. Information Technology. 2007

Dissertation Abstracts International 68-09B.

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4
Protocols for stochastic shortest path problems with dynamic learning.
Protocols for stochastic shortest path problems with dynamic learning.
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Protocols for stochastic shortest path problems with dynamic learning.

Vural. Aksakalli The Johns Hopkins University. 2007

Dissertation Abstracts International 68-04B.

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5
A bilevel optimization approach to machine learning.
A bilevel optimization approach to machine learning.
A bilevel optimization approach to machine learning.
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A bilevel optimization approach to machine learning.

Gautam. Kunapuli Rensselaer Polytechnic Institute. 2008

Dissertation Abstracts International 69-09B.

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6
Machine Learning in Automating Supply Management Maturity Ratings.
Machine Learning in Automating Supply Management Maturity Ratings.
Machine Learning in Automating Supply Management Maturity Ratings.
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Machine Learning in Automating Supply Management Maturity Ratings.

Yung-Yun. Huang ProQuest Information and Learning Co.; North Carolina State University. Operations Research. 2017

Dissertation Abstracts International 78-10B(E).

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7
Case-based reasoning for real-time traffic flow management.
Case-based reasoning for real-time traffic flow management.
Case-based reasoning for real-time traffic flow management.
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Case-based reasoning for real-time traffic flow management.

Adel Wadid. Sadek University of Virginia. 1998

Dissertation Abstracts International 59-07B.

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8
Neural network model using a genetic algorithm to perform the functions of X-bar charts.
Neural network model using a genetic algorithm to perform the functions of X-bar charts.
Neural network model using a genetic algorithm to perform the functions of X-bar charts.
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Neural network model using a genetic algorithm to perform the functions of X-bar charts.

Neal Franklin. Jackson The University of Mississippi. 1999

Dissertation Abstracts International 60-08A.

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9
Intelligent classification, simulation and control of traffic flow.
Intelligent classification, simulation and control of traffic flow.
Intelligent classification, simulation and control of traffic flow.
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Intelligent classification, simulation and control of traffic flow.

Fengxiang. Qiao Hong Kong University of Science and Technology (People's Republic of China). 2000

Dissertation Abstracts International 61-10A.

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10
Inhabitant identification from activity patterns using a graph-based data mining technique.
Inhabitant identification from activity patterns using a graph-based data mining technique.
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Inhabitant identification from activity patterns using a graph-based data mining technique.

Ritesh Indarmal. Mehta The University of Texas at Arlington. 2003

Masters Abstracts International 42-03.

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