Computational Intelligence

This present book includes a set of selected revised and extended versions of the best papers presented at the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - held in Vienna, Austria, from 17 to 19 September 2019. The authors focus on three outstanding fields of Computational Intelligence through the selected panel, namely Evolutionary Computation, Fuzzy Computation and Neural Computation. Besides presenting the recent advances of the selected areas, the book aims to aggregate new and innovative solutions for confirmed researchers and, on the other hand, to provide a source of information and/or inspiration for young interested researchers or learners in the ever-expanding and current filed of Computational Intelligence. It constitutes a precious provision of knowledge for individual researchers as well as represents a valuable sustenance for collective use in academic libraries (of universities and engineering schools) relating innovative techniques invarious fields of applications.

Inhalt

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 Classi cation.- Near Optimal Solving of the (N2-1)-Puzzle using Heuristics based on Arti cial Neural Networks.- Deep Convolutional Neural Network Processing of Images for Obstacle Avoidance.- CVaR Q-learning.- Rule Extraction from Neural Networks and Other Classi ers Applied to XSS Detection.- Introduction to Sequential Heteroscedastic Probabilistic Neural Networks.