"Matzoh Ball Soup" is a distinctive collection of personal stories, poems, and rabbinical sermons that inspires the Jewish spirit. This collaboration of many impressive figures has resulted in a heartfelt and poignant anthology that is rich in both quality and content. The selections in "Matzoh Ball Soup" have been collected as a way to help individuals understand many of life's important lessons through the Jewish perspective. The writings are divided into eight chapters that are based on identifiable Jewish topics such as Shabbat, Hanukkah, Family, High Holidays, and others. Individually,...
"Matzoh Ball Soup" is a distinctive collection of personal stories, poems, and rabbinical sermons that inspires the Jewish spirit. This collaboration ...
Computational Intelligence (CI) bezeichnet ein Teilgebiet der Kunstlichen Intelligenz, das biologische inspirierte Modelle algorithmisch umsetzt. Evolutionare Algorithmen orientieren sich an der darwinistischen Evolution und suchen mit Hilfe von Crossover, Mutation und Selektion eine optimale Losung. Die Fuzzy-Logik ermoglicht als unscharfe Logik eine kognitive Modellierung von Wissen und Inferenzprozessen. Neuronale Netze imitieren funktionale Aspekte des Gehirns fur Aufgaben wie Klassifikation und Mustererkennung. Neuere Ansatze der CI wie Reinforcement Learning ermoglichen, das...
Computational Intelligence (CI) bezeichnet ein Teilgebiet der Kunstlichen Intelligenz, das biologische inspirierte Modelle algorithmisch umsetzt. E...
This book introduces various types of self-adaptive parameters for evolutionary computation. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.
This book introduces various types of self-adaptive parameters for evolutionary computation. Besides extensive experiments, statistical tests and s...
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with...
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification...
Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for...
Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is av...
This bookintroduces numerous algorithmic hybridizations between both worlds that showhow machine learning can improve and support evolution strategies. Aftergiving an introduction to evolution strategies and machine learning, the bookbuilds the bridge between both worlds with an algorithmic and experimentalperspective.
This bookintroduces numerous algorithmic hybridizations between both worlds that showhow machine learning can improve and support evolution strategies...
This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held in Riva del Garda, Italy, in September 2016. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held i...
This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part...
This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to un...
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach.
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification an...
