000 | 05156cam a2200613Ii 4500 | ||
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001 | on1001287932 | ||
003 | OCoLC | ||
005 | 20220711203406.0 | ||
006 | m o d | ||
007 | cr cnu|||unuuu | ||
008 | 170817s2017 xxk o 001 0 eng d | ||
040 |
_aN$T _beng _erda _epn _cN$T _dIDEBK _dN$T _dEBLCP _dOCLCF _dYDX _dUMI _dDG1 _dMERUC _dMERER _dUAB |
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019 |
_a1001379151 _a1003645604 |
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020 |
_a9781119136750 _q(electronic bk.) |
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020 |
_a111913675X _q(electronic bk.) |
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020 | _z9781848218093 | ||
020 | _a9781119136736 | ||
020 | _a1119136733 | ||
020 | _z1848218095 | ||
035 |
_a(OCoLC)1001287932 _z(OCoLC)1001379151 _z(OCoLC)1003645604 |
||
037 |
_aCL0500000891 _bSafari Books Online |
||
050 | 4 | _aTK3105 | |
072 | 7 |
_aTEC _x009070 _2bisacsh |
|
082 | 0 | 4 |
_a621.319 _223 |
049 | _aMAIN | ||
245 | 0 | 0 |
_aMetaheuristics for intelligent electrical networks / _cFrédéric Héliodore, Amir Nakib, Boussaad Ismail, Salma Ouchraa, Laurent Schmitt. |
264 | 1 |
_aLondon, UK : _bISTE, Ltd. ; _aHoboken, NJ : _bWiley, _c2017. |
|
300 | _a1 online resource. | ||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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490 | 1 |
_aComputer engineering series, Metaheuristics set ; _vvolume 10 |
|
504 | _aIncludes bibliographical references and index. | ||
588 | 0 | _aOnline resource; title from PDF title page (Ebsco, viewed August 29, 2017). | |
505 | 0 | _aCover; Half-Title Page; Title Page; Copyright Page; Contents; Introduction; 1. Single Solution Based Metaheuristics; 1.1. Introduction; 1.2. The descent method; 1.3. Simulated annealing; 1.4. Microcanonical annealing; 1.5. Tabu search; 1.6. Pattern search algorithms; 1.6.1. The GRASP method; 1.6.2. Variable neighborhood search; 1.6.3. Guided local search; 1.6.4. Iterated local search; 1.7. Other methods; 1.7.1. The Nelder-Mead simplex method; 1.7.2. The noising method; 1.7.3. Smoothing methods; 1.8. Conclusion; 2. Population-based Methods; 2.1. Introduction; 2.2. Evolutionary algorithms | |
505 | 8 | _a2.2.1. Genetic algorithms2.2.2. Evolution strategies; 2.2.3. Coevolutionary algorithms; 2.2.4. Cultural algorithms; 2.2.5. Differential evolution; 2.2.6. Biogeography-based optimization; 2.2.7. Hybrid metaheuristic based on Bayesian estimation; 2.3. Swarm intelligence; 2.3.1. Particle Swarm Optimization; 2.3.2. Ant colony optimization; 2.3.3. Cuckoo search; 2.3.4. The firefly algorithm; 2.3.5. The fireworks algorithm; 2.4. Conclusion; 3. Performance Evaluation of Metaheuristics; 3.1. Introduction; 3.2. Performance measures; 3.2.1. Quality of solutions; 3.2.2. Computational effort | |
505 | 8 | _a3.2.3. Robustness3.3. Statistical analysis; 3.3.1. Data description; 3.3.2. Statistical tests; 3.4. Literature benchmarks; 3.4.1. Characteristics of a test function; 3.4.2. Test functions; 3.5. Conclusion; 4. Metaheuristics for FACTS Placement and Sizing; 4.1. Introduction; 4.2. FACTS devices; 4.2.1. The SVC; 4.2.2. The STATCOM; 4.2.3. The TCSC; 4.2.4. The UPFC; 4.3. The PF model and its solution; 4.3.1. The PF model; 4.3.2. Solution of the network equations; 4.3.3. FACTS implementation and network modification; 4.3.4. Formulation of FACTS placement problem as an optimization issue | |
505 | 8 | _a4.4. PSO for FACTS placement4.4.1. Solutions coding; 4.4.2. Binary particle swarm optimization; 4.4.3. Proposed Lévy-based hybrid PSO algorithm; 4.4.4. "Hybridization" of continuous and discrete PSO algorithms for application to the positioning and sizing of FACTS; 4.5. Application to the placement and sizing of two FACTS; 4.5.1. Application to the 30-node IEEE network; 4.5.2. Application to the IEEE 57-node network; 4.5.3. Significance of the modified velocity likelihoods method; 4.5.4. Influence of the upper and lower bounds on the velocity -> Vci of particles ci | |
505 | 8 | _a4.5.5. Optimization of the placement of several FACTS of different types (general case)4.6. Conclusion; 5. Genetic Algorithm-based Wind Farm Topology Optimization; 5.1. Introduction; 5.2. Problem statement; 5.2.1. Context; 5.2.2. Calculation of power flow in wind turbine connection cables; 5.3. Genetic algorithms and adaptation to our problem; 5.3.1. Solution encoding; 5.3.2. Selection operator; 5.3.3. Crossover; 5.3.4. Mutation; 5.4. Application; 5.4.1. Application to farms of 15-20 wind turbines; 5.4.2. Application to a farm of 30 wind turbines | |
650 | 0 |
_aSmart power grids. _97197 |
|
650 | 7 |
_aTECHNOLOGY & ENGINEERING / Mechanical. _2bisacsh _97198 |
|
650 | 7 |
_aSmart power grids. _2fast _0(OCoLC)fst01792824 _97197 |
|
655 | 4 |
_aElectronic books. _93294 |
|
700 | 1 |
_aHéliodore, Frédéric, _eauthor. _97199 |
|
700 | 1 |
_aNakib, Amir, _eauthor. _97200 |
|
700 | 1 |
_aIsmail, Boussaad, _eauthor. _97201 |
|
700 | 1 |
_aOuchraa, Salma, _eauthor. _97202 |
|
700 | 1 |
_aSchmitt, Laurent, _eauthor. _97203 |
|
776 | 0 | 8 |
_cOriginal _z1848218095 _z9781848218093 _w(OCoLC)908914278 |
830 | 0 |
_aComputer engineering series (London, England). _pMetaheuristics set ; _v10. _97204 |
|
856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119136736 _zWiley Online Library |
942 | _cEBK | ||
994 |
_a92 _bDG1 |
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999 |
_c68832 _d68832 |