Search Results - (( using complex data algorithm ) OR ( using optimization means algorithm ))

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…Adopting the medoid instead of the mean can enhance the efficiency. However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

“…To overcome this disadvantage, the Fireflies Algorithm (FA) was used because it has the ability to perform global searches and has quick convergence rate to optimize the initial clustering centers of the K-means algorithm, using a kind of weighted Euclidean distance to reduce the defects made by noise data and other uncertainties. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

“…Clustering, an unsupervised method of grouping sets of data, is used as a solution technique in various fields to divide and restructure data to become more significant and transform them into more useful information. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

“…Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction by Nor Farizan, Zakaria, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…The algorithm identified seven optimal features primarily comprising temperature and humidity parameters. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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A novel hybrid metaheuristic algorithm for short term load forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Yuhanis, Yusof, Syafiq Fauzi, Kamarulzaman

“…Findings of the study revealed that, by producing lower Root Mean Square Percentage Error (RMSPE), the GWO-LSSVM is able to outperform the identified algorithms for the data set of interest.…”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

“…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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Hybrid Metaheuristic Algorithm for Short Term Load Forecasting by Zuriani, Mustaffa, M. H., Sulaiman, Yuhanis, Yusof, Syafiq Fauzi, Kamarulzaman

“…Findings of the study revealed that, by producing lower Root Mean Square Percentage Error (RMSPE), the GWO-LSSVM is able to outperform the identified algorithms for the data set of interest.…”
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Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…The inputs of the networks are the frequency, the magnitude of the reflection coefficient and the phase of the reflection coefficient while the outputs are the dielectric constant, the loss factor and the oil content. The training data for the models were obtained from dielectric and moisture content measurements and the obtained data were fitted into the quasi-static wave Equations and optimized using MATLAB complex root finding technique to obtain the normalized conductance, susceptance and the complex permittivity of the fruitlets. …”
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Prostate cancer prediction using feedforward neural network trained with particle swarm optimizer by Jui, Julakha Jahan, Molla, M. M.Imran, Alam, Mohammad Khurshed, Ferdowsi, Asma

“…PSO is one of the novel metaheuristics and frequently used for solving several complex problems. The experimental results are evaluated using the mean, best, worst, and standard deviation (Std.) values of the fitness function and compared with other learning algorithms for FNNs, including the Salp Swarm Algorithm (SSA) and Sine Cosine Algorithm (SCA). …”
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