Search Results - (( based optimization methods algorithm ) OR ( _ optimisation data algorithm ))

An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

“…Optimisation-based methods are enormously used in the field of data classification. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation by Zhanuzak, Raiymbek, Ala'anzy, Mohammed Alaa, Othman, Mohamed, Algarni, Abdulmohsen

“…Additionally, if a VM cannot meet a cloudlet's deadline, the algorithm redirects the cloudlet to a secondary data centre and reconfigures CPU resources among VMs to ensure optimal allocation. …”
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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.

“…Benchmarking; Discrete cosine transforms; Genetic algorithms; Image coding; Image enhancement; Mean square error; Signal to noise ratio; Bayes method; Cover-image; Data hidden; Embedding capacity; Flipping methods; Least significant bits; Medium; Optimisations; Variability; Visual qualities; Steganography…”

The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

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Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

“…Its performance is compared with baseline LSTM, baseline GRU, BiLSTM, and LSTM-based particle swarm optimization (PSO) models across various error metrics. …”

An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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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. ROC Curve and statistical metrics were involved in the results validation. …”

Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and t... by Oh Lai Ching, Narong

“…Pre-experiment data is optimized based on Taguchi-grey and Flower Pollination Algorithm (FPA) methods. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance by Saidah Saad, Zikun, Huang

“…By retraining the model using the optimised training set, an optimal F1 measure of 92.7% was achieved. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

“…Grid search method was adopted to optimise the hyperparameters of the investigated base models. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor by Mohamad Nor, Ahmad Azhari

“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

Modelling and calibration of high-pressure direct injection compressed natural gas engine by Mohd Fadzil, Abdul Rahim

“…An optimal Artificial Neural Network (ANN) model is required to facilitate model-based calibration (MBC) procedure. …”
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Optimising Connectivity and Energy : The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by IZZAH NILAMSYUKRIYAH, BUANG, Kartinah, Zen, Syahrul Nizam, Junaini

“…Key topics examined include AI-enhanced adaptive data rate (ADR) methods, coding schemes based on the Chinese Remainder Theorem (CRT), and processes utilizing Variable Order Hidden Markov Models (VHMM). …”
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

“…The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

“…The optimum structure of the neural network was determined by trial and error method to obtain the optimized hidden neuron and weight values. …”
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