Search Results - (( probable optimization method algorithm ) OR ( probable optimization means algorithm ))
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. Also, convergence in the probability function of employee bees’ movement was prevented by increasing the number of route-creating tours. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…To overcome these problems this project proposes a methodology for determining consumers’ TLPs by using fuzzy C-means (FCM) clustering method and probability neural networks (PNN) classification techniques. …”
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Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm
Published 2009“…The fluctuation of obtained makespan in FGA method is less than GA method which means that it is more probable to find a better solution by FGA rather than GA.…”
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Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors
Published 2023“…Climate models; Climatology; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Mean square error; Particle swarm optimization (PSO); Principal component analysis; Stream flow; Adaptive neuro-fuzzy inference system; ANFIS-PSO; Climate index; Confidence levels; ENSO; Probability spaces; Root mean square errors; Streamflow simulations; Fuzzy inference; assessment method; El Nino-Southern Oscillation; genetic algorithm; index method; model; prediction; seasonal variation; streamflow; uncertainty analysis…”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
Published 2015“…This situation can be solved by embedding Genetic Algorithm (GA) in the network to replace back-propagation method. …”
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15
Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model
Published 2024“…This study aims to propose a framework for processing Top-k queries in UDS, where the focus is on leveraging the efficiency of the SWM, achieved through the SWMTop-kDelta algorithm. After establishing this model's rules and probability theory, a method was designed to support the Top-k processing algorithm over the SWM until the Top-k potential candidates expired. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…In the evaluation of the proposed method, the effectiveness is assessed using the metrics of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). …”
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Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm
Published 2024“…A novel approach is introduced to enhance SIBI character predictions using the K-Nearest Neighbor (K-NN) algorithm. The K-NN algorithm is employed to predict the most suitable SIBI character based on the similarity of linguistic features between input speech and existing data. …”
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Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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