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

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    Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2025
    “…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…For the model validation, we utilize widely used evaluation techniques: Mean Absolute Error, Root Mean Squared Error, Mean Absolute Percentage Error, and R-squared. …”
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  4. 4

    Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model by Yaseen, Z.M., Ebtehaj, I., Bonakdari, H., Deo, R.C., Danandeh Mehr, A., Mohtar, W.H.M.W., Diop, L., El-Shafie, A., Singh, V.P.

    Published 2017
    “…The present results have wider implications not only for streamflow forecasting purposes, but also for other hydro-meteorological forecasting variables requiring only the historical data input data, and attaining a greater level of predictive accuracy with the incorporation of the FFA algorithm as an optimization tool in an ANFIS model.…”
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    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
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    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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    Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

    Published 2022
    “…For optimum results in performance analysis, the optimal value of the MOPSO-CD was evaluated using (ZDT), (WFG), and (DTLZ) with two or three objectives over D2MOPSO, AgMOPSO, MMOPSO, and EMOSO algorithms. …”
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    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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    Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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    Structural optimization of 4-DOF agricultural robot arm by Nurul Emylia Natasya Ahmad Zakey, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim

    Published 2024
    “…Simulation of kinematic modeling is performed using MATLAB software. This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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