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Expert Systems and Probabilistic Network Models

Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods;

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Probabilistic Similarity Networks

that encode knowledge in a decision-theoretic framework. He introduces the similarity network and partition and constructs the expert system;

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Probabilistic models for computer networks

Probabilistic models for computer networks: Tools and solved problems overviews the main probabilistic tools and theory used in the;

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Computational Learning And Probabilistic Reasoning

probabilistic models that exploit the independence relationships presented in the graphs, and applications of Bayesian networks to multivariate;

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Advanced Decision-Making Methods and Applications in System Safety and Reliability Problems

, Bayesian Network approach and interval type-2 fuzzy set, advanced TOPSIS with spherical fuzzy set, and advanced BWM with neutrosophic fuzzy set and;

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Random Signals

covers three important areas: fundamentals and examples of random process models; application of probabilistic models - signal detection and;

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Probabilistic Reasoning in Multiagent Systems

probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an;

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Probabilistic Reasoning in Multiagent Systems

probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an;

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Network Reliability and Algebraic Structures

Networks of computer systems, distribution systems, and telecommunication systems play an increasingly important role in our lives. This;

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Probabilistic Reliability Analysis of Power Systems: A Student's Introduction

methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic;

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Probabilistic Reliability Analysis of Power Systems

methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic;

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Probabilistic Reliability Models

Practical Approaches to Reliability Theory in Cutting-Edge Applications Probabilistic Reliability Models helps readers understand and;

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Probabilistic Inference and Statistical Methods in Network Analysis

Probabilistic Inference and Statistical Methods in Network Analysis examines various aspects of network analysis and analysis several;

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Probabilistic Networks and Expert Systems

Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while;

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Probabilistic Graphical Models

and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks;

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Socio-Technical Risk Analysis

hybrid approach that combines deterministic (e.g., System Dynamics) and probabilistic (e.g. Bayesian Belief Network) modeling techniques. An;

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Data-Driven Computational Neuroscience

trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic;

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Practical Probabilistic Programming

trends, computer system failures, experimental outcomes, and other critical concerns. Practical Probabilistic Programming explains;

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Probabilistic Transmission System Planning

, which discuss the concepts, models, methods and data in probabilistic transmission planning. The second part, Chapters 8 to 11, addresses four;

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UAV Swarm Networks: Models, Protocols, and Systems

network models, 7-layer protocols and system integration for UAV swarm network.;

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Stochastic Models of Uncertainties in Computational Mechanics

support robust optimization, design, and updating. A probabilistic approach to uncertainties is the most powerful, efficient, and effective;

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Query Processing on Probabilistic Data

community and the Al community have studied various aspects of probabilistic relational data. Query Processing on Probabilistic Data: A Survey;

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Handbook of Probabilistic Models

that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil;

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Probabilistic Reliability Engineering

solving problems of system design. Broad and authoritative in its content, Probabilistic Reliability Engineering covers all mathematical models;

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Probability Models in Operations Research

. Probability Models in Operations Research provides a comprehensive overview of the probabilistic and stochastic modeling approaches commonly used to;

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Probability Models in Operations Research

. Probability Models in Operations Research provides a comprehensive overview of the probabilistic and stochastic modeling approaches commonly used to;

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Network Models in Economics and Finance

some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling;

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