Search Results - (((((((kant OR antiek) OR wind) OR mantis) OR cantor) OR anne) OR halted) OR planting) algorithms.

Algorithmic Beauty of Plants. by Lindenmayer, Aristid

Table of Contents: “…The Virtual Laboratory; The Algorithmic Beauty of Plants; Copyright; Preface; Contents; Chapter 1 Graphical modeling using L-systems; Chapter 2 Modeling of trees; Chapter 3 Developmental models of herbaceous plants; Chapter 4 Phyllotaxis; Chapter 5 Models of plant organs; Chapter 6 Animation of plant development; Chapter 7 Modeling of cellular layers; Chapter 8 Fractal properties of plants; Epilogue; Appendix A Software environment for plant modeling; Appendix B About the figures; Turtle interpretation of symbols; Bibliography; Index.…”
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Offshore wind energy technology by Anaya-Lara, Olimpo, Tande, John O., 1962-, Uhlen, Kjetil, 1961-, Merz, Karl, 1978-

Table of Contents: “…2.6 Power Electronic Converters for MW Wind Turbine Generators2.7 Wind Generators Compared to Conventional Power Plant; 2.8 Acknowledgements; 2.9 References; 3 Modelling and Analysis of Drivetrains in Offshore Wind Turbines; 3.1 Introduction; 3.2 Drivetrain Concepts; 3.3 Gearbox Failures; 3.4 State-of-the-art Wind Turbine Gearbox Design Codes; 3.5 Drivetrain Modelling and Analysis; 3.6 Limit State Design; 3.7 Drivetrains in Floating Wind Turbines; 3.8 Condition Monitoring and Inspection; 3.9 Drivetrains in Fault Conditions; 3.10 5-MW Reference Offshore Drivetrain; 3.11 References.…”
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Theory of randomized search heuristics : foundations and recent developments

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Algorithmic composition : a guide to composing music with Nyquist by Simoni, Mary Hope

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Pathway modeling and algorithm research

Table of Contents: “…PATHWAY MODELING AND ALGORITHM RESEARCH; PATHWAY MODELING AND ALGORITHM RESEARCH; Contents; Preface; Biological Pathways and Their Modeling; Abstract; 1. …”
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Machine Learning Algorithms and Applications. by Srinivas, Mettu

Table of Contents: “…2.4 Dataset Generation -- 2.5 Results -- 2.6 Conclusion -- Acknowledgment -- References -- 3 A Wind Speed Prediction System Using Deep Neural Networks -- 3.1 Introduction -- 3.2 Methodology -- 3.3 Results and Discussions -- 3.4 Conclusion -- References -- 4 Res-SE-Net: Boosting Performance of ResNets by Enhancing Bridge Connections -- 4.1 Introduction -- 4.2 Related Work -- 4.3 Preliminaries -- 4.4 Proposed Model -- 4.5 Experiments -- 4.6 Results -- 4.7 Conclusion -- References -- 5 Sakshi Aggarwal, Navjot Singh and K.K. …”
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Graph algorithms and applications 3

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Iterative Algorithms For Multilayer Optimizing Control. by Brdys, Mietek A.

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Network and discrete location : models, algorithms, and applications by Daskin, Mark S., 1952-

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Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS) by Amrane, Fayssal, Chaiba, Azeddine

Table of Contents: “…Robustness Tests7 for Mode 1, Mode 2 Mode 3 -- A-Mode 1 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- B-Mode 2 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- C-Mode 3 (Novel IDPC based on T1-FLC, T2-FLC NFC): -- 7. WIND-SYSTEM PERFORMANCES RECAPITULATION UNDER SIX (06) PROPOSED IDPC ALGORITHMS -- CONCLUSION -- NOTES -- REFERENCES -- General Conclusion -- 5.1. …”
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Coherent Doppler Wind Lidars in a Turbulent Atmosphere. by Banakh, V. A. (Viktor Arsentʹevich)

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Diffuse algorithms for neural and neuro-fuzzy networks : with applications in control engineering and signal processing by Skorohod, Boris A.

Table of Contents: “…Front Cover; Diffuse Algorithms for Neural and Neuro-Fuzzy Networks; Copyright Page; Contents; List of Figures; List of Tables; Preface; 1 Introduction; 1.1 Separable Models of Plants and Training Problems Associated With Them; 1.1.1 Separable Least Squares Method; 1.1.2 Perceptron With One Hidden Layer; 1.1.3 Radial Basis Neural Network; 1.1.4 Neuro-Fuzzy Network; 1.1.5 Plant Models With Time Delays; 1.1.6 Systems With Partly Unknown Dynamics; 1.1.7 Recurrent Neural Network; 1.1.8 Neurocontrol; 1.2 The Recursive Least Squares Algorithm With Diffuse and Soft Initializations.…”
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Algorithmic and artificial intelligence methods for protein bioinformatics

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Meta-heuristic and evolutionary algorithms for engineering optimization by Bozorg-Haddad, Omid, 1974-, Solgi, Mohammad, 1989-, Loaiciga, Hugo A.

Table of Contents: “…Overview of optimization -- Introduction to meta-heuristic and evolutionary algorithms -- Pattern search (PS) -- Genetic algorithm (GA) -- Simulated annealing (SA) -- Tabu search (TS) -- Ant colony optimization (ACO) -- Particle swarm optimization (PSO) -- Differential evolution (DE) -- Harmony search (HS) -- Shuffled frog-leaping algorithm (SFLA) -- Honey-bee mating optimization (HBMO) -- Invasive weed optimization (IWO) -- Central force optimization (CFO) -- Biogeography-based optimization (BBO) -- Firefly algorithm (FA) -- Gravity search algorithm (GSA) -- Bat algorithm (BA) -- Plant propagation algorithm (PPA) -- Water cycle algorithm (WCA) -- Symbiotic organisms search (SOS) -- Comprehensive evolutionary algorithm (CEA).…”
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Condition Monitoring with Vibration Signals : Compressive Sampling and Learning Algorithms for Rotating Machines. by Nandi, Asoke K.

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Turing's vision : the birth of computer science by Bernhardt, Chris

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A Polygeneration Process Concept for Hybrid Solar and Biomass Power Plant : Simulation, Modeling, and Optimization. by Sahoo, Umakanta

Table of Contents: “…6.3 Primary Energy Savings on the Polygeneration Process in an HSB Thermal Power Plant6.4 Optimization; 6.4.1 Objective Functions; 6.4.2 Decision Variable and Constraints; 6.4.3 Genetic Algorithm (GA); 6.5 Cost Analysis; 6.6 Analysis Of Polygeneration Process in an HSB Thermal Power Plant for Power, Cooling, and Desalination; 6.7 Optimization of the Polygeneration System; 6.8 Cost Analysis of a Polygeneration System; Exercise; References; Appendix 1; Nomenclature; Greek; Subscripts; Acronyms; Appendix 2; EES Software Coding; Appendix 3; Multiple Choice Questions (MCQ) with Answers; Answers.…”
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Adventures in Raspberry Pi by Philbin, Carrie Anne

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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning : Incorporate New Powerful ML Algorithms Such As Deep Reinforcement Learning for Games. by Lanham, Micheal

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Intelligence emerging : adaptivity and search in evolving neural systems by Downing, Keith L.

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