Search Results - (((((((ant OR anti) OR mantic) OR walted) OR cantor) OR anne) OR wind) OR win) algorithms.

Algorithmic trading : winning strategies and their rationale / by Chan, Ernest P., 1966-

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Ant Colony Optimization and Constraint Programming. by Solnon, Christine

Table of Contents: “…Constraint programming; 1.1.2. Ant colony optimization; 1.1.3. Constraint programming with ant colony optimization; Chapter 2. …”
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Building winning algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading / by Davey, Kevin J., 1966-

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Theory of randomized search heuristics : foundations and recent developments

Table of Contents: “…Runtime Analysis of Evolutionary Algorithms for Discrete Optimization Peter S. Oliveto and Xin Yao; 3. …”
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Algorithmic composition : a guide to composing music with Nyquist by Simoni, Mary Hope

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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: “…4 Fixed and Floating Offshore Wind Turbine Support Structures4.1 Introduction; 4.2 Bottom-fixed Support Structures; 4.3 Floating Support Structures; 4.4 Design Considerations; 4.5 Conceptual Design; 4.6 Loads in the Marine Environment; 4.7 Global Dynamic Analysis of Offshore Wind Turbines; 4.8 Conclusions; 4.9 References; 5 Offshore Wind Turbine Controls; 5.1 Control Objectives, Sensors and Actuators; 5.2 Control Algorithms; 5.3 A Linear Aeroelastic Loads Model for Closed-loop System Dynamics; 5.4 Basic Rotor Speed Control in Operating Regions I and II; 5.5 Active Damping and Load Reduction.…”
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Nature-inspired optimization algorithms by Yang, Xin-She

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Swarm intelligence and bio-inspired computation : theory and applications

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Bayesian modeling using WinBUGS by Ntzoufras, Ioannis, 1973-

Table of Contents: “…Introduction to Bayesian inference -- Markov chain Monte Carlo algorithms in Bayesian inference -- WinBUGS software : introduction, setup, and basic analysis -- WinBUGS software : illustration, results, and further analysis -- Introduction to Bayesian models : normal models -- Incorporating categorical variables in normal models and further modeling issues -- Introduction to generalized linear models : binomial and Poisson data -- Models for positive continuous data, count data, and other GLM-based extensions -- Bayesian hierarchical models -- The predictive distribution and model checking -- Bayesian model and variable evaluation -- Appendix A : Model specification via directed acyclic graphs : the DOODLE menu -- Appendix B : The batch mode : running a model in the background using scripts -- Appendix C : Checking convergence using CODA/BOA -- Appendix D : Notation summary.…”
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Ant colony optimization by Dorigo, Marco

Table of Contents: “…Preface; Acknowledgments; 1 -- From Real to Artificial Ants; 2 -- The Ant Colony Optimization Metaheuristic; 3 -- Ant Colony Optimization Algorithms for the Traveling Salesman Problem; 4 -- Ant Colony Optimization Theory; 5 -- Ant Colony Optimization for NP-Hard Problems; 6 -- AntNet: An ACO Algorithm for Data Network Routing; 7 -- Conclusions and Prospects for the Future; Appendix: Sources of Information about the ACO Field; References; Index.…”
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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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Swarm Intelligence Algorithms : Modifications and Applications. by Slowik, Adam

Table of Contents: “…-- 1.2.3 Pseudo-code of standard ACO algorithm -- 1.3 Modified variants of ant colony optimization -- 1.3.1 Elitist ant systems -- 1.3.2 Ant colony system -- 1.3.3 Max-min ant system -- 1.3.4 Rank based ant systems -- 1.3.5 Continuous orthogonal ant systems…”
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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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Metaheuristic optimization for the design of automatic control laws by Sandou, Guillaume

Table of Contents: “…Ant colony optimization…”
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Modern anti-windup synthesis : control augmentation for actuator saturation by Zaccarian, Luca

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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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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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