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Automatic programming (Computer science) --- Real-time programming --- Software. --- Systeemtheorie. --- Controleleer. --- Real-time programming. --- Automatic program construction (Computer science) --- Computer programming --- Real-time data processing

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This handbook offers a comprehensive treatise on Grammatical Evolution (GE), a grammar-based Evolutionary Algorithm that employs a function to map binary strings into higher-level structures such as programs. GE's simplicity and modular nature make it a very flexible tool. Since its introduction almost twenty years ago, researchers have applied it to a vast range of problem domains, including financial modelling, parallel programming and genetics. Similarly, much work has been conducted to exploit and understand the nature of its mapping scheme, triggering additional research on everything from different grammars to alternative mappers to initialization. The book first introduces GE to the novice, providing a thorough description of GE along with historical key advances. Two sections follow, each composed of chapters from international leading researchers in the field. The first section concentrates on analysis of GE and its operation, giving valuable insight into set up and deployment. The second section consists of seven chapters describing radically different applications of GE. The contributions in this volume are beneficial to both novices and experts alike, as they detail the results and researcher experiences of applying GE to large scale and difficult problems. Topics include: • Grammar design • Bias in GE • Mapping in GE • Theory of disruption in GE · Structured GE · Geometric semantic GE · GE and semantics · Multi- and Many-core heterogeneous parallel GE · Comparing methods to creating constants in GE · Financial modelling with GE · Synthesis of parallel programs on multi-cores · Design, architecture and engineering with GE · Computational creativity and GE · GE in the prediction of glucose for diabetes · GE approaches to bioinformatics and system genomics · GE with coevolutionary algorithms in cybersecurity · Evolving behaviour trees with GE for platform games · Business analytics and GE for the prediction of patient recruitment in multicentre clinical trials.

Evolutionary programming (Computer science) --- Automatic programming (Computer science) --- Automatic program construction (Computer science) --- Computer programming --- Artificial intelligence. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers

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This practical monograph gives a comprehensive introduction to the concepts and languages of the IEC 61131 standard used to program industrial control systems. The second edition of this established reference covers the latest developments of the IEC 61131 standard. The text and the numerous examples have been extensively updated and present the state of the art of program¬ming industrial automation systems. A summary of the special requirements in programming industrial automation systems and the corresponding features in the IEC 61131-3 standard makes the book suitable for students as well as PLC experts. The material is presented in an easy-to-understand form using numerous examples, illustrations and summary tables. The book also includes a purchaser's guide. Karl-Heinz John Degree in Com¬puter Science 1981, degree thesis on microprogramming. Since 1984 at infoteam Software GmbH, co-owner and chief executive officer (CEO), his areas of responsibility include the development of IEC 61131 programming systems, such as OpenPCS. He is also a founder member of PLCopen (www.plcopen.org) and vice-president of ASQF (www.asqf.de). Michael Tiegelkamp Degree in Computer Science 1988, degree thesis on PLC architectures. From 1988 to 1994 at infoteam Software GmbH, project manager and head of marketing, responsible for PLC programming systems. Since 1994 at SIEMENS AG, pro¬ject manager for development and later group manager for product definition in the field of SIMATIC, since 2004 various manager positions in the field of low-voltage energy distribution.

Automation -- Data processing. --- Mechanical Engineering --- Engineering & Applied Sciences --- Mechanical Engineering - General --- Automation --- Automatic programming (Computer science) --- Automation. --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Automatic program construction (Computer science) --- Engineering. --- Special purpose computers. --- Computer programming. --- Control engineering. --- Control. --- Special Purpose and Application-Based Systems. --- Programming Techniques. --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Computer programming --- Software engineering. --- Computer science. --- Control and Systems Theory. --- Computer software engineering --- Engineering --- Informatics --- Science --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Special purpose computers --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Programming

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This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method can be applied to a wide range of machine learning architectures and applications to represent complex feature dependencies explicitly when machine learning cannot achieve this by itself. Industrial applications can use the proposed technique to improve their predictions.

Engineering. --- Computational Intelligence. --- Pattern Recognition. --- Quantitative Finance. --- Optical pattern recognition. --- Finance. --- Ingénierie --- Reconnaissance optique des formes (Informatique) --- Finances --- Engineering & Applied Sciences --- Computer Science --- Time-series analysis. --- Prediction theory. --- Computer programming. --- Psycholinguistics. --- Evolutionary programming (Computer science) --- Automatic programming (Computer science) --- Data mining. --- Genetic programming (Computer science) --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Automatic program construction (Computer science) --- Language, Psychology of --- Language and languages --- Psychology of language --- Speech --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Forecasting theory --- Analysis of time series --- Psychological aspects --- Psychology --- Programming --- Pattern recognition. --- Economics, Mathematical. --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Economics --- Mathematical economics --- Econometrics --- Mathematics --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Construction --- Industrial arts --- Technology --- Methodology --- Computer programming --- Genetic algorithms --- Database searching --- Linguistics --- Thought and thinking --- Coding theory --- Stochastic processes --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Funding --- Funds --- Currency question --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Economics, Mathematical .