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Wyniki wyszukiwania dla: EVOLUTIONARY ALGORITHM
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Distributed Evolutionary Algorithm for Path Planning in Navigation Situation
PublikacjaThis article presents the use of a multi-population distributed evolutionary algorithm for path planning in navigation situation. The algorithm used is with partially exchanged population and migration between independently evolving populations. In this paper a comparison between a multi-population and a classic single-population algorithm takes place. The impact on the ultimate solution has been researched. It was shown that using...
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Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach
PublikacjaIn the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared....
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Parameters of evolutionary algorithm in problem of collision avoidance at sea
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Evolutionary algorithm and decisional DNA for multiple travelling salesman problem
PublikacjaIn the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algorithm II), to solve multiple optimization...
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Genetic operators of evolutionary algorithm in problem of collision avoidance at sea
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Pareto Task Assignments by an Adaptive Quantum-based Evolutionary Algorithm AQMEA
PublikacjaW pracy scharakteryzowano state_of_the_art w zakresie kwantowych algorytmów ewolucyjnych. Scharakteryzowano zasady efektywnego projektowania tej klasy algorytmów genetycznych. Podano wyniki uzyskane za pomocą kwantowego algorytmu ewolucyjnego AQMEA w zakresie wyznaczanie przydziałów zadań optymalnych w sensie Pareto.
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Comparison of Single and Multi-Population Evolutionary Algorithm for Path Planning in Navigation Situation
PublikacjaIn this paper a comparison of single and multi-population evolutionary algorithm is presented. Tested algorithms are used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of single-population and multi-population evolutionary algorithm is described....
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublikacjaAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublikacjaIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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Application of a modified evolutionary algorithm for the optimization of data acquisition to improve the accuracy of a video-polarimetric system
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High level synthesis with adaptive evolutionary algorithm for solving reliability and thermal problems in reconfigurable microelectronic systems.
PublikacjaPraca dotyczy badań efektywności adaptacyjnego algorytmu ewolucyjnego (AEA)zastosowanego do syntezy wysokiego poziomu układów cyfrowych CMOS w celu zredukowania rozpraszanej przez nie mocy. W wyniku obniżenia poziomu mocy pobieranej przez układ mikroelektroniczny uzyskuje się zmniejszenie szczytowej i średniej temperatury układu scalonego co z kolei prowadzi do wzrostu niezawodności całego systemu. Podczas przeprowadzonych...
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Reducing average and peak temperatures of VLSI CMOS circuits by means of evolutionary algorithm applied to high level synthesis.
PublikacjaW pracy przedstawiono adaptacyjny algorytm ewolucyjny zastosowany do syntezy wysokiego poziomu układów cyfrowych CMOS w celu zredukowania pobieranej przez nie mocy. Prowadzi to do redukcji szczytowej i średniej temperatury układu scalonego. Dzięki temu uzyskuje się wzrost niezawodności projektowanych układów scalonych.
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Comparison of tuning procedures based on evolutionary algorithm for multi-region fuzzy-logic PID controller for non-linear plant
PublikacjaThe paper presents a comparison of tuning procedures for a multi-region fuzzy-logic controller used for nonlinear process control. This controller is composed of local PID controllers and fuzzy-logic mechanism that aggregates local control signals. Three off-line tuning procedures are presented. The first one focuses on separate tuning of local PID controllers gains in the case when the parameters of membership functions of fuzzy-logic...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublikacjaNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Termination functions for evolutionary path planning algorithm
PublikacjaIn this paper a study of termination functions (stop criterion) for evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Five...
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Multicriteria Evolutionary Weather Routing Algorithm in Practice
PublikacjaThe Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid-propulsion or motor-driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization...
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Impact of Initial Population on Evolutionary Path Planning Algorithm
PublikacjaIn this paper an impact of initial population on evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal shippaths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Four tests are performed....
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Impact of Initial Population on Evolutionary Path Planning Algorithm
PublikacjaIn this paper an impact of initial population on evolutionary path planning algorithm is presented. Tested algorithm is used to determine close to optimal ship paths in collision avoidance situation. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. For the simulation purposes a close to real tested environment is created. Four tests are performed....
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Evolutionary Algorithms in MPLS network designing
PublikacjaMPLS technology become more and more popular especially in core networks giving great flexibility and compatibility with existing Internet protocols. There is a need to optimal design such networks and optimal bandwidth allocation. Linear Programming is not time efficient and does not solve nonlinear problems. Heuristic algorithms are believed to deal with these disadvantages and the most promising of them are Evolutionary Algorithms....
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Extinction Event Concepts for the Evolutionary Algorithms
PublikacjaThe main goal of this present paper is to propose a structure for a tool helping to determine how algorithm would react in a real live application, by checking it's adaptive capabilities in an extreme situation. Also a different idea of an additional genetic operator is being presented. As Genetic Algorithms are directly inspired by evolution, extinction events, which are elementary in our planet's development history, became...
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OPTIMISING RIG DESIGN FOR SAILING YACHTS WITH EVOLUTIONARY MULTIOBJECTIVE ALGORITHM
PublikacjaThe paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used...
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Hybrid evolutionary partitioning algorithm for heat transfer enhancement in VLSI circuits
PublikacjaW niniejszym artykule przedstawiono metodę pozwalającą na polepszenie transferu ciepła z układu scalonego do otoczenia poprzez zwiększenie liczby połączeń zewnętrznych, co pozwoliło na polepszenie przewodności cieplnej układu scalonego. Dla osiągnięcia tego celu opracowano nowy, hybrydowy, ewolucyjny algorytm podziału (ang. Hybrid Evolutionary Partitioning Algorithm - HEPA). Obliczenia przeprowadzone dla wybranych przykładów testowych...
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Experimental research on evolutionary path planning algorithm with fitness function scaling for collision scenarios
PublikacjaThis article presents typical ship collision scenarios, simulated using the evolutionary path planning system and analyses the impact of the fitness function scaling on the quality of the solution. The function scaling decreases the selective pressure, which facilitates leaving the local optimum in the calculation process and further exploration of the solution space. The performed investigations have proved that the use of scaling...
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Multi-criterion decision making in distributed systems by quantum evolutionary algorithms
PublikacjaDecision making by the AQMEA (Adaptive Quantum-based Multi-criterion Evolutionary Algorithm) has been considered for distributed computer systems. AQMEA has been extended by a chromosome representation with the registry of the smallest units of quantum information. Evolutionary computing with Q-bit chromosomes has been proofed to characterize by the enhanced population diversity than other representations, since individuals represent...
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The Use of Evolutionary Algorithms for Optimization in the Modern Entrepreneurial Economy: Interdisciplinary Perspective
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Intelligent Optimization of Hard-Turning Parameters Using Evolutionary Algorithms for Smart Manufacturing
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Design and optimisation of combinational digital circuits using modified evolutionary algorithm.Projektowanie i optymalizacja kombinacyjnych układów cyfrowych przy użyciu zmodyfikowanego algorytmu ewolucyjnego.
PublikacjaW pracy przedstawiono możliwości projektowania i optymalizacji układów kombinacyjnych przy użyciu zmodyfikowanych algorytmów ewolucyjnych. Modyfikacja algorytmów polega na wprowadzeniu chromosomów wielowarstwowych i operatorów działających na nich. Wyniki projektowania czterech układów kombinacyjnych uzyskanych uzyskane tą metodą porównano z następującymi metodami opisanymi w literaturze jak: Mapy Karnaugh, metoda Quine-McCluskey...
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Evolutionary Sets of Safe Ship Trajectories: improving the method by adjusting evolutionary techniques and parameters
PublikacjaThe paper presents some of the evolutionary techniques used by the evolutionary sets of safe ship trajectories method. In general, this method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (here the set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories are...
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Multi-criterion, evolutionary and quantum decision making in complex systems
PublikacjaMulti-criterion, evolutionary and quantum decision making supported by the Adaptive Quantum-based Multi-criterion Evolutionary Algorithm (AQMEA) has been considered for distributed complex systems. AQMEA had been developed to the task assignment problem, and then it has been applied to underwater vehicle planning as another benchmark three-criterion optimization problem. For evaluation of a vehicle trajectory three criteria have...
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Evolutionary Sets of Safe Ship Trajectories: problem dedicated operators
PublikacjaThe paper presents the optimization process of the evolutionary sets of safe ship trajectories method, with a focus on its problem-dedicated operators. The method utilizes a customized evolutionary algorithm to solve a constrained optimization problem. This problem is defined as finding a set of cooperating trajectories (a set is an evolutionary individual) of all the ships involved in the encounter situation. The resulting trajectories...
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Evolutionary music composition system with statistically modeled criteria
PublikacjaThe paper concerns an original evolutionary music composition system. On the basis of available solutions, we have selected a finite set of music features which appear to have a key impact on the quality of composed musical phrases. Evaluation criteria have been divided into rule-based and statistical sub-sets. Elements of the cost function are modeled using a Gaussian distribution defined by the expected value and variance obtained...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublikacjaThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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Path planning algorithm for ship collisions avoidance in environment with changing strategy of dynamic obstacles
PublikacjaIn this paper a path planning algorithm for the ship collision avoidance is presented. Tested algorithm is used to determine close to optimal ship paths taking into account changing strategy of dynamic obstacles. For this purpose a path planning problem is defined. A specific structure of the individual path and fitness function is presented. Principle of operation of evolutionary algorithm and based on it dedicated application...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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EVOLUTIONARY MULTI–OBJECTIVE WEATHER ROUTING OF SAILBOATS
PublikacjaThe paper presents a multi-objective method, which optimises the route of a sailboat. The presented method makes use of an evolutionary multi-objective (EMO) algorithm, which performs the optimisation according to three objective functions: total passage time, a sum of all course alterations made during the voyage and the average angle of heel. The last two of the objective functions reflect the navigator’s and passenger’s comfort,...
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Mean Crossover in evolutionary path planning method for maritime collision avoidance
PublikacjaAbstract: This paper presents the use of mean crossover genetic operator for path planning using evolutionary algorithm for collision avoidance on sea. Mean crossover ensures widening of the possible solutions' set that can be achieved in comparison to exchange crossover variant. The research shown, that the mean crossover allows to achieve results independent from the initial generation and quicker transition of thealgorithm from...
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Porównanie algorytmów MGA i NGA do projektowania i optymlizacji kombinacyjnych układów cyfrowych z algorytmem MLCEA.
PublikacjaW artykule zaprezentowano porównanie algorytmów ewolucyjnych do projektowania i optymalizacji kombinacyjnych układów cyfrowych. Porównano algorytmy MGA (Multiobjective Genetic Algorithm) i NGA (Genetic Algorithm with N-cardinality Reprezentation) z utworzonym algorytmem MLCEA (Multi-Layer Chromosome Evolutionary Algorithm), bazującym na reprezentacji osobników w postaci chromosomów wielowarstwowych. Otrzymane wyniki dla algorytmu...
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Genetic Programming for Workload Balancing in the Comcute Grid System
PublikacjaA genetic programming paradigm is implemented for reliability optimization in the Comcute grid system design. Chromosomes are generated as the program functions and then genetic operators are applied for finding Pareto-suboptimal task assignment and scheduling. Results are compared with outcomes obtained by an adaptive evolutionary algorithm.
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Multi-objective Weather Routing with Customised Criteria and Constraints
PublikacjaThe paper presents a weather routing algorithm utilising a multi-objective optimisation with constraints, namely the Multi-objective Evolutionary Weather Routing Algorithm (MEWRA). In the proposed approach weather route recommendations can be made simultaneously e.g. for passage time, fuel consumption and safety of passage by means of Pareto optimisation. The sets of criteria and constraints in the optimisation process are fully...
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Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublikacjaA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublikacjaFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Rotational Design Space Reduction for Cost-Efficient Multi-Objective Antenna Optimization
PublikacjaCost-efficient multi-objective design of antenna structures is presented. Our approach is based on design space reduction algorithm using auxiliary single-objective optimization runs and coordinate system rotation. The initial set of Pareto-optimal solutions is obtained by optimizing a response surface approximation model established in the reduced space using coarse-discretization EM simulation data. The optimization engine is...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublikacjaThe paper presents a method of incorporating decision maker preferences into multi-objective meta-heuristics. It is based on tradeoffcoefficients and extends their applicability from bi-objective to multi-objective. The method assumes that a decision maker specifies a priori each objective’s importance as a weight interval. Based on this, w-dominance relation is introduced, which extends Pareto dominance. By replacing reference...
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Komputerowa weryfikacja układów cyfrowych CMOS utworzonych z podukładów zasilanych ze źródeł o różnych wartościach napięcia
PublikacjaW pracy zaprezentowano wyniki komputerowej weryfikacji cyfrowego układu CMOS utworzonego z klastrów, z których każdy jest zasilany odpowiednio malejącymi wartościami napięć. Zbiór klastrów został utworzony przy pomocy algorytmu ECA (Evolutionary Clustering Algorithm) dla potrzeb redukcji mocy pobieranej ze źródła zasilającego. Otrzymane rozwiązanie, charakteryzujące się zmniejszeniem zapotrzebowania na moc, nie powoduje pogorszenia...
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Fast Multi-Objective Antenna Design Through Variable-Fidelity EM Simulations
PublikacjaA technique for fast multi-objective antenna optimization is introduced. A kriging interpolation surrogate constructed from sampled coarse-mesh EM simulations is utilized by multi-objective evolutionary algorithm (MOEA) to obtain the initial Pareto front approximation. The surrogate is defined in a subset of the original design space, determined by means of independently optimized individual objectives. Response correction techniques...
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublikacjaIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublikacjaW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublikacjaIn this paper, a novel meta-heuristic method for evaluation of digital filter stability is presented. The proposed method is very general because it allows one to evaluate stability of systems whose characteristic equations are not based on polynomials. The method combines an efficient evolutionary algorithm represented by the particle swarm optimization and the phase analysis of a complex function in the characteristic equation....
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Weather Hazard Avoidance in Modeling Safety of Motor-Driven Ship for Multicriteria Weather Routing
PublikacjaWeather routing methods find the most suitable ocean?s route for a vessel, taking into account changeable weather conditions and navigational constraints. In the multicriteria approach based on the evolutionary SPEA algorithm one is able to consider a few constrained criteria simultaneously. The approach applied for a ship with hybrid propulsions has already been presented by one of the authors on previous TransNav?2009. This time...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...