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training algorithms are implemented in Visual Studio 2005, and tested with universally accepted data files. It is observed that the Improvement;
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University" and the Power System Analysis Toolbox. This implementation generates the nose curves, used for voltage stability analysis, for IEEE 30;
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experimental programmes (2000-2004). The EC-funded Marie Curie Research Training Network AMGISS (Advanced Modelling of Ground Improvement on Soft Soils;
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in torque were reduced significantly.Radial basis and feed forward neural networks werecompared for off-line and on-line training, trainingtime;
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This new book presents and discusses current research in the study of computer networks. Topics discussed include an in-depth analysis;
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in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges;
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culture. It, in turn, needs Six Sigma, Lean and TOC methodologies to be the fuel for the improvement engine that drives the company forward. Any;
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? If so, this is the book for you! With straight-forward guidance on research design and data collection, as well as social network analysis;
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Pareto charts and Failure Mode Effects Analysis (FMEA).;
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of network knowledge, the accumulation of network skills, and the improvement of professionalism. Through the complete process from the elaboration;
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comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It'll guide;
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The second edition of this bestselling book, 'Return on Investment in Training and Performance Improvement Programs,' guides you through a;
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Methodology; Human Factors in Quality Improvement, Random Safety Audits, Root Cause Analysis, and Failure Mode and Effects Analysis; Collaboration;
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instructional practice? In what ways does good data collection and analysis feed into successful continuous improvement and holistic systems thinking;
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. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics;
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. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics;
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optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat;
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improvement--no need to rely on expensive training in a new methodology. Free video training and a 90-day trial version of QI Macros for Excel can;
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controller. Feed forward neural network architecture is chosen for the design of controller, which is trained by a popular back propagation algorithm;
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Improvement is fundamental to the competitiveness of networks and requires the participating firms to collaborate in identifying and;
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machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;
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machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;
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in genome sequencing and analysis, public and private genomic resources and how all this information is leading to direct outcomes for plant;
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in genome sequencing and analysis, public and private genomic resources and how all this information is leading to direct outcomes for plant;
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changes in teaching practices. Written by participants in a series of ground-breaking social network analysis (SNA) workshops, Researching and;
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fodder by microorganisms and animal by-products. Analysis of contamination by persistent organic pollutants and toxic metals follows in part two;
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Einde inhoud
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