Search Results - (( data distribution means algorithm ) OR ( data optimization method algorithm ))
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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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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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.]
Published 2017“…Researchers then performed data preprocessing on the data. Afterwards, data mining algorithms were applied in order to forecast electric load. …”
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Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning
Published 2024“…In the era of data-driven decision-making, managing dynamic data streams characterized by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. …”
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Assessment of landsat 7 scan line corrector-off data gap-filling methods for seagrass distribution mapping
Published 2015“…For optimal performance of the GNSPI algorithm, cloud and shadow in the primary and auxiliary images had to be removed by cloud removal methods prior to filling data gaps. …”
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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region
Published 2024“…Through the utilization of openly accessible fine-resolution data and employing the RF algorithm, the research demonstrated promising outcomes in the identification of optimal predictor-algorithm combinations for forest AGB mapping. …”
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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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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…More specifically, we use multi-objective models that are the mean-entropy-entropy (MEE). The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
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Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter
Published 2013“…The results report improvements over the conventional methods in terms of mean square errors.…”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture
Published 2021“…Thus, to address the controller placement problem (CPP) in a distributed 5G network, we proposed an efficient, heuristic multi-objective optimization approach, using dynamic capacitated controller placement problem (DCCPP). …”
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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs
Published 2025“…This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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