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    Wyświetlanie 1-13 z 13
    Tytuł:
    Using GA for evolving weights in neural networks
    Autorzy:
    Hameed, Wafaa Mustafa
    Kanbar, Asan Baker
    Powiązania:
    https://bibliotekanauki.pl/articles/118057.pdf
    Data publikacji:
    2019
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    genetic algorithm
    neural network
    crossover
    mutation
    algorytm genetyczny
    sieć neuronowa
    skrzyżowanie
    mutacja
    Opis:
    This article aims at studying the behavior of different types of crossover operators in the performance of Genetic Algorithm. We have also studied the effects of the parameters and variables (crossover probability (Pc), mutation probability (Pm), population size (popsize) and number of generation (NG) for controlling the algorithm. This research accumulated most of the types of crossover operators these types are implemented on evolving weights of Neural Network problem. The article investigates the role of crossover in GAs with respect to this problem, by using a comparative study between the iteration results obtained from changing the parameters values (crossover probability, mutation rate, population size and number of generation). From the experimental results, the best parameters values for the Evolving Weights of XOR-NN problem are NG = 1000, popsize = 50, Pm = 0.001, Pc = 0.5 and the best operator is Line Recombination crossover.
    Źródło:
    Applied Computer Science; 2019, 15, 3; 21-33
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of artificial neural network and genetic algorithm to healthcarewaste prediction
    Autorzy:
    Arabgol, S.
    Ko, H. S.
    Powiązania:
    https://bibliotekanauki.pl/articles/91848.pdf
    Data publikacji:
    2013
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    artificial neural network
    ANN
    application
    hospital
    genetic algorithm
    GA
    healthcare waste
    Opis:
    Prompt and proper management of healthcare waste is critical to minimize the negative impact on the environment. Improving the prediction accuracy of the healthcare waste generated in hospitals is essential and advantageous in effective waste management. This study aims at developing a model to predict the amount of healthcare waste. For this purpose, three models based on artificial neural network (ANN), multiple linear regression (MLR), and combination of ANN and genetic algorithm (ANN-GA) are applied to predict the waste of 50 hospitals in Iran. In order to improve the performance of ANN for prediction, GA is applied to find the optimal initial weights in the ANN. The performance of the three models is evaluated by mean squared errors. The obtained results have shown that GA has significant impact on optimizing initial weights and improving the performance of ANN.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2013, 3, 4; 243-250
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Applying artificial intelligence algorithms in MOBA games
    Autorzy:
    Wiśniewski, M.
    Niewiadomski, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/92952.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
    Tematy:
    multiplayer online battle arena
    MOBA
    artificial intelligence
    AI
    genetic algorithm
    GA
    computer game
    computer game agents
    bots
    Opis:
    Multiplayer Online Battle Arena games focus mainly on struggles between two teams of players. An increasing level of cyberbullying [1] discourages new players from the game and they often chose a different option, that is, a match against opponents controlled by the computer. The behavior of artificial foes can be dynamically fitted to user’s needs, in particular with regard to the difficulty of the game. In this paper we explore different approaches to provide an intelligent behavior of bots basing on more human-like combat predictions rather than instant, scripted behaviors.
    Źródło:
    Studia Informatica : systems and information technology; 2016, 1-2(20); 53-64
    1731-2264
    Pojawia się w:
    Studia Informatica : systems and information technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction and optimization of tower mill grinding power consumption based on GA-BP neural network
    Autorzy:
    Wang, Ziyang
    Hou, Ying
    Sobhy, Ahmed
    Powiązania:
    https://bibliotekanauki.pl/articles/27323660.pdf
    Data publikacji:
    2023
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    tower mill
    grinding power consumption
    energy saving
    genetic algorithm
    BP neural network
    Opis:
    Grinding is commonly responsible for the liberation of valuable minerals from host rocks but can entail high costs in terms of energy and medium consumption, but a tower mill is a unique power-saving grinding machine over traditional mills. In a tower mill, many operating parameters affect the grinding performance, such as the amount of slurry with a known solid concentration, screw mixer speed, medium filling rate, material-ball ratio, and medium properties. Thus, 25 groups of grinding tests were conducted to establish the relationship between the grinding power consumption and operating parameters. The prediction model was established based on the backpropagation “BP” neural network, further optimized by the genetic algorithm GA to ensure the accuracy of the model, and verified. The test results show that the relative error of the predicted and actual values of the backpropagation “BP” neural network prediction model within 3% was reduced to within 2% by conducting the generic algorithm backpropagation “GA-BP” neural network. The optimum grinding power consumption of 41.069 kWh/t was obtained at the predicted operating parameters of 66.49% grinding concentration, 301.86 r/min screw speed, 20.47% medium filling rate, 96.61% medium ratio, and 0.1394 material-ball ratio. The verifying laboratory test at the optimum conditions, produced a grinding power consumption of 41.85 kWh/t with a relative error of 1.87%, showing the feasibility of using the genetic algorithm and BP neural network to optimize the grinding power consumption of the tower mill.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2023, 59, 6; art. no. 172096
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Decentralized PID control by using GA optimization applied to a quadrotor
    Autorzy:
    Hasseni, S. E. I.
    Abdou, L.
    Powiązania:
    https://bibliotekanauki.pl/articles/384905.pdf
    Data publikacji:
    2018
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    quadrotor
    non-linear systems
    decentralized control
    PID
    optimization
    genetic algorithm
    systemy nieliniowe
    kontrola zdecentralizowana
    optymalizacja
    algorytm genetyczny
    Opis:
    Quadrotors represent an effective class of aerial robots because of their abilities to work in small areas. We suggested in this research paper to develop an algorithm to control a quadrotor, which is a nonlinear MIMO system and strongly coupled, by a linear control technique (PID), while the parameters are tuned by the Genetic Algorithm (GA). The suggested technique allows a decentralized control by decoupling the linked interactions to effect angles on both altitude and translation position. Moreover, the using a meta-heuristic technique enables a certain ability of the system controllers design without being limited by working on just the small angles and stabilizing just the full actuated subsystem. The simulations were implemented in MATLAB/Simulink tool to evaluate the control technique in terms of dynamic performance and stability. Although the controllers design (PID) is simple, it shows the effect of the proposed technique in terms of tracking errors and stability, even with large angles, subsequently, high velocity response and high dynamic performances with practically acceptable rotors speed.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 2; 33-44
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    GA based optimal planning of VAR sources using Fast Voltage Stability Index method
    Autorzy:
    Bhattacharyya, B.
    Rani, S.
    Vais, I. R.
    Bharti, P. I.
    Powiązania:
    https://bibliotekanauki.pl/articles/140784.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    active power loss
    FVSI method
    genetic algorithm
    operating cost
    reactive power planning
    weak nodes
    Opis:
    This paper presents a novel approach for reactive power planning of a connected power network. Reactive power planning is nothing but the optimal usage of all reactive power sources i.e., transformer tap setting arrangements, reactive generations of generators and shunt VAR compensators installed at weak nodes. Shunt VAR compensator placement positions are determined by a FVSI (Fast Voltage Stability Index) method. Optimal setting of all reactive power reserves are determined by a GA (genetic algorithm) based optimization method. The effectiveness of the detection of the weak nodes by the FVSI method is validated by comparing the result with two other wellknown methods of weak node detection like Modal analysis and the L-index method. Finally, FVSI based allocation of VAR sources emerges as the most suitable method for reactive power planning.
    Źródło:
    Archives of Electrical Engineering; 2016, 65, 4; 789-802
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Comparative study of GA & DE algorithm for the economic operation of a power system using FACTS devices
    Autorzy:
    Bhattacharyya, B.
    Gupta, V. K.
    Kumar, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/141459.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    FACTS devices
    line power flow
    FACTS devices & its optimal locations
    genetic algorithm
    differential evolution technique
    Opis:
    The problem of improving the voltage profile and reducing power loss in electrical networks must be solved in an optimal manner. This paper deals with comparative study of Genetic Algorithm (GA) and Differential Evolution (DE) based algorithm for the optimal allocation of multiple FACTS (Flexible AC Transmission System) devices in an interconnected power system for the economic operation as well as to enhance loadability of lines. Proper placement of FACTS devices like Static VAr Compensator (SVC), Thyristor Controlled Switched Capacitor (TCSC) and controlling reactive generations of the generators and transformer tap settings simultaneously improves the system performance greatly using the proposed approach. These GA & DE based methods are applied on standard IEEE 30 bus system. The system is reactively loaded starting from base to 200% of base load. FACTS devices are installed in the different locations of the power system and system performance is observed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. GA and DE based algorithm is then applied to find the amount of magnitudes of the FACTS devices. Finally the comparison between these two techniques for the placement of FACTS devices are presented.
    Źródło:
    Archives of Electrical Engineering; 2013, 62, 4; 541-552
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Improving estimation accuracy of metallurgical performance of industrial flotation process by using hybrid genetic algorithm – artificial neural network (GA-ANN)
    Autorzy:
    Allahkarami, E.
    Salmani Nuri, O.
    Abdollahzadeh, A.
    Rezai, B.
    Maghsoudi, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/109424.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    artificial neural network
    genetic algorithm
    prediction
    copper flotation
    Opis:
    In this study, a back propagation feed forward neural network, with two hidden layers (10:10:10:4), was applied to predict Cu grade and recovery in industrial flotation plant based on pH, chemical reagents dosage, size percentage of feed passing 75 μm, moisture content in feed, solid ratio, and grade of copper, molybdenum, and iron in feed. Modeling is performed basing on 92 data sets under different operating conditions. A back propagation training was carried out with initial weights randomly mode that may lead to trapping artificial neural network (ANN) into the local minima and converging slowly. So, the genetic algorithm (GA) is combined with ANN for improving the performance of the ANN by optimizing the initial weights of ANN. The results reveal that the GA-ANN model outperforms ANN model for predicting of the metallurgical performance. The hybrid GA-ANN based prediction method, as used in this paper, can be further employed as a reliable and accurate method, in the metallurgical performance prediction.
    Źródło:
    Physicochemical Problems of Mineral Processing; 2017, 53, 1; 366-378
    1643-1049
    2084-4735
    Pojawia się w:
    Physicochemical Problems of Mineral Processing
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Administration-and communication-aware IP core mapping in scalable multiprocessor system-on-chips via evolutionary computing
    Autorzy:
    Guderian, F.
    Schaffer, R.
    Fettweis, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/91539.pdf
    Data publikacji:
    2012
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    intellectual property
    IP
    IP core
    mapping
    system-on-chips
    mixed-integer linear programming
    MILP
    genetic algorithm
    GA
    administration
    communication
    Opis:
    In this paper, an efficient mapping of intellectual property (IP) cores onto a scalable multiprocessor system-on-chip with a k-ary 2-mesh network-on-chip is performed. The approach is to place more affine IP cores closer to each other reducing the number of traversed routers. Affinity describes the pairwise relationship between the IP cores quantified by an amount of exchanged communication or administration data. A genetic algorithm (GA) and a mixed-integer linear programming (MILP) solution use the affinity values in order to optimize the IP core mappings. The GA generates results faster and with a satisfactory quality relative to MILP. Realistic benchmark results demonstrate that a tradeoff between administration and communication affinity significantly improves application performance.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 133-146
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    WTHD minimisation in hybrid multilevel inverter using biogeographical based optimisation
    Autorzy:
    Kavitha, R.
    Thottungal, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/141212.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    biogeographical based optimisation
    BBO
    genetic algorithm
    GA
    bacterial foraging algorithm
    BFA
    weighted total harmonics distortion
    WTHD
    optimal minimisation of total harmonic
    OMTHD
    selective harmonic elimination
    SHE
    Opis:
    Harmonic minimisation in hybrid cascaded multilevel inverter involves complex nonlinear transcendental equation with multiple solutions. Hybrid cascaded multilevel can be implemented using reduced switch count when compared to traditional cascaded multilevel inverter topology. In this paper Biogeographical Based Optimisation (BBO) technique is applied to Hybrid multilevel inverter to determine the optimum switching angles with weighted total harmonic distortion (WTHD) as the objective function. Optimisation based on WTHD combines the advantage of both OMTHD (Optimal Minimisation of Total Harmonic Distortion) and SHE (Selective Harmonic Elimination) PWM. WTHD optimisation has the benefit of eliminating the specific lower order harmonics as in SHEPWM and minimisation of THD as in OMTHD. The simulation and experimental results for a 7 level multilevel inverter were presented. The results indicate that WTHD optimization provides both elimination of lower order harmonics and minimisation of Total Harmonic Distortion when compared to conventional OMTHD and SHE PWM. Experimental prototype of a seven level hybrid cascaded multilevel inverter is implemented to verify the simulation results.
    Źródło:
    Archives of Electrical Engineering; 2014, 63, 2; 187-196
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method
    Autorzy:
    Chang, Y.-C.
    Chiu, M.-C.
    Xie, J.-L.
    Powiązania:
    https://bibliotekanauki.pl/articles/178126.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    finite element method
    polynomial neural network model
    genetic algorithm
    group method of data handling
    reciprocating compressor
    optimization
    Opis:
    Industry often utilizes acoustical hoods to block noise emitted from reciprocating compressors. However, the hoods are large and bulky. Therefore, to diminish the size of the compressor, a compact discharge muffler linked to the compressor outlet is considered. Because the geometry of a reciprocating compressor is irregular, COMSOL, a finite element analysis software, is adopted. In order to explore the acoustical performance, a mathematical model is established using a finite element method via the COMSOL commercialized package. Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. During the optimization, various noise abatement strategies such as a reverse expansion chamber at the outlet of the discharge muffler and an inner extended tube inside the discharge muffler, will be assessed by using the artificial neural network in conjunction with the GA optimizer. Consequently, the discharge muffler that is optimally shaped will decrease the noise of the reciprocating compressor.
    Źródło:
    Archives of Acoustics; 2017, 42, 2; 189-197
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Shape Optimisation of Multi-Chamber Acoustical Plenums Using BEM, Neural Networks, and GA Method
    Autorzy:
    Chang, Y.-C.
    Cheng, H.-C.
    Chiu, M.-C.
    Chien, Y.-H.
    Powiązania:
    https://bibliotekanauki.pl/articles/177780.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    boundary element method
    plenum
    centre-opening baffle
    polynomial neural network model
    group method of data handling
    optimisation
    genetic algorithm
    Opis:
    Research on plenums partitioned with multiple baffles in the industrial field has been exhaustive. Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, two kinds of multi-chamber plenums (Case I: a two-chamber plenum that is partitioned with a centre-opening baffle; Case II: a three-chamber plenum that is partitioned with two centre-opening baffles) within a fixed space are assessed. In order to speed up the assessment of optimal plenums hybridized with multiple partitioned baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fit with a series of real data – input design data (baffle dimensions) and output data approximated by BEM data in advance. To assess optimal plenums, a genetic algorithm (GA) is applied. The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.
    Źródło:
    Archives of Acoustics; 2016, 41, 1; 43-53
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The comparison of genetic algorithms which solve orienteering problem using complete and incomplete graph
    Porównanie algorytmów genetycznych rozwiązujących Orienteering Problem przy pomocy grafu pełnego i niepełnego
    Autorzy:
    Ostrowski, K.
    Koszelew, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/341187.pdf
    Data publikacji:
    2011
    Wydawca:
    Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
    Tematy:
    graf niepełny
    graf pełny
    sieć transportowa
    OP
    GA
    algorytm genetyczny
    orienteering problem
    transport network
    genetic algorithm
    incomplete graph
    complete graph
    Opis:
    The purpose of this work was to compare two forms of genetic algorithm (complete and incomplete graph version) which solves Orienteering Problem (OP). While in most papers concerning OP graph is complete and satisfies triangle inequality, in our versions such assumptions may not be satisfied. It could be more practical as transport networks are graphs which do not have to satisfy those conditions. In such cases, graphs are usually complemented with fictional edges before they can be used by classic OP solving algorithms which operate on complete graphs. This paper answers the question: Is it better (in terms of results quality and time consumption) to transform graphs to classic OP form before running algorithm (complete graph version) or to solve OP on graphs without any assumptions and changes (incomplete graph version)? The computer experiment was conducted on the real transport network in Poland and its results suggest that it is worth checking both versions of the algorithm on concrete networks.
    Celem pracy było porównanie dwóch odmian algorytmu (wersja dla grafu pełnego i niepełnego) rozwiązujących Orienteering Problem (OP). W większości artykułów dotyczących OP graf jest pełny, a jego krawędzie spełniają nierówność trójkąta, natomiast w naszej wersji takie założenia mogą nie być spełnione. Może to być bardziej praktyczne ponieważ sieci transportowe są grafami, ktore nie muszą spełniać tych warunków. W takich przypadkach grafy są zazwyczaj uzupełniane fikcyjnymi krawędziami, a następnie działają na nich algorytmy rozwiązujące klasyczną wersje OP, które operują na grafie pełnym. Artykuł odpowiada na pytanie: czy pod względem jakości wyników i czasu obliczeń lepiej jest przekształcać graf do klasycznej formy OP przed uruchomieniem algorytmu w wersji dla grafu pełnego czy rozwiązywać OP na grafie niezmienionym i nie spełniającym dodatkowych założeń (wersja dla grafu niepełnego)? Eksperyment został przeprowadzony na prawdziwej sieci transportowej w Polsce, a jego wyniki sugerują, że warto sprawdzać obie wersje algorytmu na konkretnych sieciach.
    Źródło:
    Zeszyty Naukowe Politechniki Białostockiej. Informatyka; 2011, 8; 61-77
    1644-0331
    Pojawia się w:
    Zeszyty Naukowe Politechniki Białostockiej. Informatyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-13 z 13

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