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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…The HFPSO technique hybridizes the Firefly Optimization (FFO) algorithm and the Particle Swarm Optimization (PSO) method to improve the exploitation and exploration strategies and enhance the convergence rate. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems by Alomoush, Alaa A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alrosan, Ayat, Alomoush, Waleed, Alissa, Khalid

“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…The approach is based on optimization of selected test case from test suite T. …”
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Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

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.

“…Moreover, the LSTM model hyperparameters are optimized using the GSA optimization technique. To evaluate the robustness of the proposed method, 15 prediction samples are generated to calculate the uncertainty levels (95% CI) of the predicted RUL. …”

Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

“…For the system sum rate, the results of the increase in the number of users with a fixed number of 128 and 512 BS antennas show that the proposed method achieved up to 24% and 35% respectively compared to the regular BD algorithm. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency by Khalaji Assadi, Morteza

“…The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation by Hannan M.A., Sebastian G., Al-Shetwi A.Q., Ker P.J., Rahman S.A., Mansor M., Muttaqi K.M., Uddin M.

“…The traditional and time-consuming method of deriving membership functions (MFs) is avoided by utilizing adaptive MFs created from the fitness function evaluation results, which are incorporated into voltage error and rate of change of voltage error for input and output. …”

Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

“…The second method performs optimization of filterbanks in cepstral feature extraction based on evolutionary algorithms. …”
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Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties by Siti Zubaidah, Adnan

“…Several other strategies pertaining to achieve desired CSD with minimum amount of fine crystals were deployed. The optimization algorithm was employed in order to determine the optimal set-point trajectory for closed-loop control. …”
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Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection by Al-Tashi, Q., Shami, T.M., Abdulkadir, S.J., Akhir, E.A.P., Alwadain, A., Alhussain, H., Alqushaibi, A., Rais, H.M.D., Muneer, A., Saad, M.B., Wu, J., Mirjalili, S.

“…The effectiveness of the LMuMOGWO is validated on 12 conventional UCI benchmark datasets and compared with two existing variants of MOGWO, BMOGWO-S (based sigmoid), BMOGWO-V (based tanh) as well as Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization (BMOPSO). …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…From a dimensionality reduction evaluation aspect, the average misclassification error of the proposed method in low-rank feature space is 9.6% and same error rate for three other well-known feature extraction methods is 21.21%. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

Particle Swarm Optimised Controller for Solid-State Transfer Switch Towards Fast Power Transfer and PQ Mitigation by Sebastian G., Hannan M.A., Al-Shetwi A.Q., Ker P.J., Muttaqi K.M., Uddin M.N.

Comparison And Assessment Of Methods Used To Estimate Egfr In Ckd Patients: The Role Of Clinical Pharmacist And Direct Medical Costs by Abdulla, Aljasmi Saba Mohsen Mohamed

“…This study aimed to evaluate GFR estimating algorithms for medication dosing in CKD patients. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq by Yaseen, Z.M., Jaafar, O., Deo, R.C., Kisi, O., Adamowski, J., Quilty, J., El-Shafie, A.

“…In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. …”
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