Search Results - (( java adaptation optimization algorithm ) OR ( based validation learning algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…Text preprocessing ensures consistent data representation and facilitates validation. The Machine Learning algorithm, comprising Random Forest, Linear Regression, XGBoost, SVM, and Stacking Ensemble, is embedded in the system for job position predictions based on the analysed data. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm by Ashraf, Erum

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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks by Sadiq, A., Yahya, N.

“…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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Suicide and self-harm prediction based on social media data using machine learning algorithms by Abdulrazak Yahya, Saleh, Fadzlyn Nasrini, Mostapa

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Wavelet network based online sequential extreme learning machine for dynamic system modeling by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

“…Wavelet network (WN) has been introduced in many applications of dynamic systems modeling with different learning algorithms. In this paper an online sequential extreme learning machine (OSELM) algorithm adopted as training procedure for wavelet network based on serial-parallel nonlinear autoregressive exogenous (NARX) model. …”
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…The first improvement includes the use of Opposition Based Learning (OBL) at initialization phase of SSA to improve its population diversity in the search space. …”
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Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning by Taotao, Xu, Musdi, Shanat, Brendan Chan, Kah Le, Wei, Zhang

“…The application of Luoshan shadow puppet elements in creative goods can break through the single communication path of shadow play and make the communication process of Luoshan shadow play art more vivid and 3D. In this paper, based on the design of modeling elements of mountain shadow puppets, the characteristics of visual elements of shadow puppets creative goods are analyzed, and an intelligent design algorithm of shadow puppets creative goods based on deep learning (DL) is innovatively proposed. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Flood mapping based on novel ensemble modeling involving the deep learning, Harris Hawk optimization algorithm and stacking based machine learning by Costache R., Pal S.C., Pande C.B., Islam A.R.M.T., Alshehri F., Abdo H.G.

“…The flood sample was divided into training (70%) and validating (30%) sample, meanwhile the prediction ability of flood conditioning factors was tested through the Correlation-based Feature Selection method. …”

A high-performance neural network algorithm using a Legendre ensemble-based extreme learning machine for solving fractional partial differential equations by Isah, Ibrahim Onimisi, Senu, Norazak, Ahmadian, Ali

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A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L.