Recent Advances in Soft Computing  [electronic resource] : Proceedings of 23rd International Conference on Soft Computing (MENDEL 2017) Held in Brno, Czech Republic, June 20-22, 2017 /
Matoušek, Radek.editor.
Soft computing is a formal area of computer science and an important aspect of artificial intelligence. Professor Lotfi A. Zadeh introduced the first definition of soft computing in the early 1990s: "Soft computing principles differs from hard (conventional) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation". The role model for soft computing is the human mind and its cognitive abilities. Techniques used for solving problems with this soft computing approach include but are not limited to fuzzy logic, neural computing, evolutionary computation, swarm intelligence, machine learning, etc. Image processing is a complex process, in which image processing routines and domain-dependent interpretation steps often alternate. In many cases image processing has to be extensively intelligent regarding the tolerance of imprecision and uncertainty. A typical application is computer vision in robotics. It is about taking concepts from nature and applying them to the design of real-world engineered systems. This proceeding book presents selected papers from the MENDEL conference held in Brno, Czech Republic in June 2017. It includes three chapters that present recent advances in soft computing including intelligent image processing. The MENDEL conference was established in 1995 and is named after the scientist and Augustinian priest Gregor J. Mendel, who discovered the famous Laws of Heredity. The main aim of the conference is to create an opportunity for students, academics and researchers to exchange ideas and novel research methods on a yearly basis.
Solving Sudoku‘s by Evolutionary Algorithms with Preprocessing -- Weak Ties and How to Find Them -- Robustness and Evolutionary Dynamic Optimisation of Airport Security Schedules -- Enhanced Archive for SHADE -- Adaptation of Sport Training Plans by Swarm Intelligence -- On the Influence of Localisation and Communication Error on the Behaviour of a Swarm of AUVs -- Spam Detection Using Linear Genetic Programming -- Optimization of Protein Mixture Filtration -- Accelerated Genetic Programming -- Hybrid Multi-objective PSO for Filter-based Feature Selection -- Scalability of GPA-ES Algorithm -- Comparison of Three Novelty Approaches to Constants (Ks) Handling in Analytic Programming Powered by SHADE -- Proposal of a New Swarm Optimization Method Inspired in Bison Behaviour -- Stochastic Heuristics for Knapsack Problems -- Waste Processing Facility Location Problem by Stochastic Programming: Models and Solutions -- Randomization of Individuals Selection in Differential Evolution -- Grammatical Evolution for Classification into Multiple Classes -- A Spiking Model of Desert Ant Navigation Along a Habitual Route -- The Application Perspective of Izhikevich Spiking Neural Model - The Initial Experimental Study -- Fuzzy Granular Calculations for the Sematic Web Using Some Mathematical Morphology Methods -- Exploring the Map Equation: Community Structure Detection in Unweighted Undirected Networks -- One of the Possible Ways to Find Partial Dependencies in Multidimensional Data -- Emergent Phenomena in Complex Systems -- Utilization of Machine Learning in Vibrodiagnostics -- Deep Analytics Based on Triathlon Athletes Blogs and News -- Weighted Multilateration in Volumetry of CNC Machine Tools -- Numerical Solving Linear Systems of Stiff Delay Differential Equations with Constant Delays -- Dynamic Generalized Berge-Zhukovskii Equilibrium -- Fuzzy Logic Control Application for the Risk Quatification of Projects for Automation.
Soft computing is a formal area of computer science and an important aspect of artificial intelligence. Professor Lotfi A. Zadeh introduced the first definition of soft computing in the early 1990s: "Soft computing principles differs from hard (conventional) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation". The role model for soft computing is the human mind and its cognitive abilities. Techniques used for solving problems with this soft computing approach include but are not limited to fuzzy logic, neural computing, evolutionary computation, swarm intelligence, machine learning, etc. Image processing is a complex process, in which image processing routines and domain-dependent interpretation steps often alternate. In many cases image processing has to be extensively intelligent regarding the tolerance of imprecision and uncertainty. A typical application is computer vision in robotics. It is about taking concepts from nature and applying them to the design of real-world engineered systems. This proceeding book presents selected papers from the MENDEL conference held in Brno, Czech Republic in June 2017. It includes three chapters that present recent advances in soft computing including intelligent image processing. The MENDEL conference was established in 1995 and is named after the scientist and Augustinian priest Gregor J. Mendel, who discovered the famous Laws of Heredity. The main aim of the conference is to create an opportunity for students, academics and researchers to exchange ideas and novel research methods on a yearly basis.
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.