This paper describes methods for calculating the most likely values of link flows in networks with incomplete data. The object is to present a thorough and rigorous treatment of maximum entropy flow estimation methods and to develop a methodological framework capable of handling different types of network problems. A multiple probability space conditional entropy approach is described for the general network problem. Results are presented and discussed for an example network intended for water supply
This paper proposes a maximum-entropy based multi-objective genetic algorithm approach for the desig...
The problem of obtaining optimal designs of water distribution systems using diameters selected from...
Evolutionary algorithms are used widely in optimization studies on water distribution networks. The ...
This paper describes methods for calculating the most likely values of link flows in networks with i...
This paper was prompted by growing evidence that Shannon's measure of uncertainty can be used as a s...
A maximum entropy (MaxEnt) framework is developed to predict mean flow rates in hydraulic pipe, elec...
The concept of a “flow network”—a set of nodes and links which carries one or more flows—unites many...
The concept of a flow network - a set of nodes connected by flow paths - encompasses many different ...
We compare the application of Bayesian inference and the maximum entropy (MaxEnt) method for the ana...
A maximum entropy (MaxEnt) method is developed to predict flow rates or pressure gradients in hydrau...
Robustness of water distribution networks is related to their connectivity and topological structure...
This paper considers the problem and appropriateness of filling-in missing conditional probabilities...
Some problems occurring in Expert Systems can be resolved by employing a causal (Bayesian) network a...
This book is an introduction to maximum-entropy models of random graphs with given topological prope...
This paper proposes a maximum entropy-based multi-objective genetic algorithm approach for the desig...
This paper proposes a maximum-entropy based multi-objective genetic algorithm approach for the desig...
The problem of obtaining optimal designs of water distribution systems using diameters selected from...
Evolutionary algorithms are used widely in optimization studies on water distribution networks. The ...
This paper describes methods for calculating the most likely values of link flows in networks with i...
This paper was prompted by growing evidence that Shannon's measure of uncertainty can be used as a s...
A maximum entropy (MaxEnt) framework is developed to predict mean flow rates in hydraulic pipe, elec...
The concept of a “flow network”—a set of nodes and links which carries one or more flows—unites many...
The concept of a flow network - a set of nodes connected by flow paths - encompasses many different ...
We compare the application of Bayesian inference and the maximum entropy (MaxEnt) method for the ana...
A maximum entropy (MaxEnt) method is developed to predict flow rates or pressure gradients in hydrau...
Robustness of water distribution networks is related to their connectivity and topological structure...
This paper considers the problem and appropriateness of filling-in missing conditional probabilities...
Some problems occurring in Expert Systems can be resolved by employing a causal (Bayesian) network a...
This book is an introduction to maximum-entropy models of random graphs with given topological prope...
This paper proposes a maximum entropy-based multi-objective genetic algorithm approach for the desig...
This paper proposes a maximum-entropy based multi-objective genetic algorithm approach for the desig...
The problem of obtaining optimal designs of water distribution systems using diameters selected from...
Evolutionary algorithms are used widely in optimization studies on water distribution networks. The ...