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Studies in Computational Intelligence : 11th International Joint Conference, IJCCI 2019, Vienna, Austria, September 17-19, 2019, Revised Selected Papers - Alejandro Linares-Barranco

Studies in Computational Intelligence

11th International Joint Conference, IJCCI 2019, Vienna, Austria, September 17-19, 2019, Revised Selected Papers

By: Alejandro Linares-Barranco (Editor), Kurosh Madani (Editor), Kevin Warwick (Editor), Juan Julian Merelo (Editor), Jonathan Garibaldi (Editor)

Hardcover | 2 July 2021

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Part I: Evolutionary Computation Theory and Applications.- Niching-based Feature Selection with Multi-Tree Genetic Programming for Dynamic Flexible Job Shop Scheduling.- Building Market Timing Strategies using Trend Representative Testing and Computational Intelligence Metaheuristics.- Hybrid Strategy Coupling EGO and CMA-ES for Structural Topology Optimization in Statics and Crashworthiness.- An Empirical Study on Insertion and Deletion Mutation in Cartesian Genetic Programming.- Handling Complexity in Some Typical Problems of Distributed Systems by using Self-organizing Principles.- Part II: Fuzzy Computation Theory and Applications.- Markov Decision Processes with Fuzzy Risk-sensitive Rewards: The Best Coherent Risk Measures under Risk Averse Utilities.- Correlation Analysis via Intuitionistic Fuzzy Modal and Aggregation Operators.- Fuzzy Geometric Approach to Collision Estimation under Gaussian Noise in Human-robot Interaction.- Predicting Cardiovascular Death with Automatically Designed Fuzzy Logic Rule-based Models.- Part III: Neural Computation Theory and Applications.- Neural Models to Quantify the Determinants of Truck Fuel Consumption.- Towards a Class-aware Information Granulation for Graph Embedding and Classification.- Near Optimal Solving of the (N2-1)-Puzzle using Heuristics based on Artificial Neural Networks.- Deep Convolutional Neural Network Processing of Images for Obstacle Avoidance.- CVaR Q-learning.- Rule Extraction from Neural Networks and Other Classifiers Applied to XSS Detection.- Introduction to Sequential Heteroscedastic Probabilistic Neural Networks.

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