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This book is focused on fractional order systems. Historically, fractional calculus has been recognized since the inception of regular calculus, with the first written reference dated in September 1695 in a letter from Leibniz to L’Hospital. Nowadays, fractional calculus has a wide area of applications in areas such as physics, chemistry, bioengineering, chaos theory, control systems engineering, and many others. In all those applications, we deal with fractional order systems in general. Moreover, fractional calculus plays an important role even in complex systems and therefore allows us to develop better descriptions of real-world phenomena. On that basis, fractional order systems are ubiquitous, as the whole real world around us is fractional. Due to this reason, it is urgent to consider almost all systems as fractional order systems.

complexity --- cuckoo search --- magnetic resonance imaging --- fractional calculus --- musical signal --- pinning synchronization --- Fourier transform --- optimal randomness --- fractional-order system --- Mittag-Leffler function --- meaning --- parameter --- diffusion-wave equation --- anomalous diffusion --- Laplace transform --- time-varying delays --- mass absorption --- swarm-based search --- fractional --- adaptive control --- time series --- Hurst exponent --- fractional derivative --- control --- PID --- global optimization --- reaction–diffusion terms --- audio signal processing --- Caputo derivative --- harmonic impact --- fractional complex networks --- heavy-tailed distribution --- impulses --- long memory --- linear prediction

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“Engineering Fluid Dynamics 2018”. The topic of engineering fluid dynamics includes both experimental as well as computational studies. Of special interest were submissions from the fields of mechanical, chemical, marine, safety, and energy engineering. We welcomed both original research articles as well as review articles. After one year, 28 papers were submitted and 14 were accepted for publication. The average processing time was 37.91 days. The authors had the following geographical distribution: China (9); Korea (3); Spain (1); and India (1). Papers covered a wide range of topics, including analysis of fans, turbines, fires in tunnels, vortex generators, deep sea mining, as well as pumps.

fluid structure interaction (FSI) --- numerical methods --- axial gap --- impeller --- radiation noise --- natural ventilation --- ventilation performance --- Computational Fluid Dynamics (CFD) --- experimental research --- hot streak --- disc thickness --- fire --- circumferential groove casing treatment --- blade wrap angle --- sweep and lean --- computational fluid dynamics (CFD) --- OpenFOAM --- gas turbine --- fire propagation --- disc spacing distance --- hydraulic collecting --- thermosyphon --- wind tunnel --- flow control --- source term --- leading edge --- flow around cylinder --- vortex generators --- plug-holing --- noise spectrum --- CGCT-blade integrated optimization --- dimensional analysis --- deep sea mining --- heat transfer --- abnormal blade installation angle --- axial fan --- rotating stall --- optimized design --- orthogonal test --- fluid dynamics --- simulation and modeling --- aerodynamic noise --- centrifugal pump --- suction flow field --- two-stage axial fan --- cavitation inception --- evaporation and condensation --- numerical simulation --- CFD simulation --- aspect ratio --- evacuation --- tunnel slope --- Tesla turbine --- vortex induced vibration (VIV) ratio --- global optimization --- volume of fluid --- blade exit angle --- acoustic energy --- tunnel vehicle fire --- multiphase flow --- distribution characteristic --- unsteady heat release rate --- hydrodynamic response --- manganese nodules exploitation --- isentropic efficiency

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Computational intelligence is a general term for a class of algorithms designed by nature's wisdom and human intelligence. Computer scientists have proposed many computational intelligence algorithms with heuristic features. These algorithms either mimic the evolutionary processes of the biological world, mimic the physiological structure and bodily functions of the organism,

individual updating strategy --- integrated design --- global optimum --- flexible job shop scheduling problem --- whale optimization algorithm --- EHO --- bat algorithm with multiple strategy coupling (mixBA) --- multi-objective DV-Hop localization algorithm --- optimization --- rock types --- variable neighborhood search --- biology --- average iteration times --- CEC2013 benchmarks --- slicing tree structure --- firefly algorithm (FA) --- benchmark --- single loop --- evolutionary computation --- memetic algorithm --- normal cloud model --- 0-1 knapsack problems --- elite strategy --- diversity maintenance --- material handling path --- artificial bee colony algorithm (ABC) --- urban design --- entropy --- evolutionary algorithms (EAs) --- monarch butterfly optimization --- numerical simulation --- architecture --- set-union knapsack problem --- Wilcoxon test --- convolutional neural network --- global position updating operator --- particle swarm optimization --- computation --- minimum load coloring --- topology structure --- adaptive multi-swarm --- minimum total dominating set --- mutation operation --- shape grammar --- greedy optimization algorithm --- ?-Hilbert space --- genetic algorithm --- large scale optimization --- large-scale optimization --- NSGA-II-DV-Hop --- constrained optimization problems (COPs) --- first-arrival picking --- transfer function --- SPEA 2 --- stochastic ranking (SR) --- wireless sensor networks (WSNs) --- acceleration search --- convergence point --- fuzzy c-means --- evolutionary algorithm --- success rates --- Artificial bee colony --- particle swarm optimizer --- random weight --- range detection --- adaptive weight --- large-scale --- automatic identification --- cloud model --- swarm intelligence --- evolutionary multi-objective optimization --- DV-Hop algorithm --- bat algorithm (BA) --- Friedman test --- quantum uncertainty property --- facility layout design --- local search --- deep learning --- Y conditional cloud generator --- benchmark functions --- discrete algorithm --- dispatching rule --- DE algorithm --- nonlinear convergence factor --- energy-efficient job shop scheduling --- t-test --- evolution --- dimension learning --- global optimization --- confidence term --- elephant herding optimization --- moth search algorithm --- evolutionary

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Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc.

Automatic Voltage Regulation system --- Chaotic optimization --- Fractional Order Proportional-Integral-Derivative controller --- Yellow Saddle Goatfish Algorithm --- two-stage method --- mono and multi-objective optimization --- multi-objective optimization --- optimal design --- Gough–Stewart --- parallel manipulator --- performance metrics --- diversity control --- genetic algorithm --- bankruptcy problem --- classification --- T-junctions --- neural networks --- finite elements analysis --- surrogate --- beam improvements --- beam T-junctions models --- artificial neural networks (ANN) limited training data --- multi-objective decision-making --- Pareto front --- preference in multi-objective optimization --- aeroacoustics --- trailing-edge noise --- global optimization --- evolutionary algorithms --- nearly optimal solutions --- archiving strategy --- evolutionary algorithm --- non-linear parametric identification --- multi-objective evolutionary algorithms --- availability --- design --- preventive maintenance scheduling --- encoding --- accuracy levels --- plastics thermoforming --- sheet thickness distribution --- evolutionary optimization --- genetic programming --- control --- differential evolution --- reusable launch vehicle --- quality control --- roughness measurement --- machine vision --- machine learning --- parameter optimization --- distance-based --- mutation-selection --- real application --- experimental study --- global optimisation --- worst-case scenario --- robust --- min-max optimization --- optimal control --- multi-objective optimisation --- robust design --- trajectory optimisation --- uncertainty quantification --- unscented transformation --- spaceplanes --- space systems --- launchers

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Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems.

electricity markets --- economic dispatch --- optimization --- maximum capacity --- online operation --- power system --- unit commitment --- circuit breaker --- network modeling --- optimal power flow --- wind and solar energies --- gas insulated switchgear --- partial discharges --- electromagnetic wave propagation --- UHF measurement --- Security-Constraint Unit Commitment --- sensitivity factors --- user cuts --- power line communication (PLC) --- energy storage management --- vehicle to grid (V2G) --- smart grid --- multi-objective optimization --- population-based intelligent optimization algorithm --- multi-behavior combination --- algorithm framework --- Economic load dispatch (ELD) --- dragonfly algorithm --- metaheuristic --- particle swarm optimization --- cold-thermal-electricity integrated energy system --- multi-energy complementation --- feasible interval of load rate --- multi-objective --- multi time scales --- optimize operation --- earthing --- earthing system --- optimisation --- Ansys Maxwell --- sensitivity analysis --- touch voltage --- non-linear programming --- security-constrained OPF --- preventive control --- corrective control --- post-contingency overflow --- transmission line --- thermal inertia --- Three-phase optimal power flow --- voltage regulation --- distributed generation --- distribution transformer taps --- linear OPF problem --- shift-factors --- line outage distribution factors --- security-constrained --- corrective formulation --- preventive formulation --- klystron --- IOT --- resotrode --- efficiency --- microwave --- bunching --- computer simulation --- global optimization --- power quality disturbances --- classification --- feature selection --- swarm optimization --- support vector machine --- genetic algorithm --- K-NN algorithm --- decision tree --- S-transform --- optimization techniques --- hydroelectric --- renewable energy --- MCDM --- fuzzy theory --- FANP --- TOPSIS --- quadratically constrained quadratic programming --- contingency constrained optimal power flow --- isolated hybrid microgrid system (IHμGS) --- solar tower (ST) --- biodiesel power generator (BDPG) --- frequency regulation --- butterfly optimization technique (BOA) --- microgrid energy management --- electric vehicle --- microgrid --- energy efficiency