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Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi by Mohammadi, Maryam

“…Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed models. Metaheuristic approaches namely genetic algorithm, particle swarm optimization, artificial bee colony, simulated annealing, and imperialist competitive algorithm are adopted for the optimization procedures. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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A Systematic Review of Metaheuristic Algorithms in Human Activity Recognition : Applications, Trends, and Challenges by John Deutero, Kisoi, Norfadzlan, Yusup, Syahrul Nizam, Junaini

“…Metaheuristic algorithms have emerged as promising techniques for optimizing human activity recognition (HAR) systems. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

“…In this work, triethanolamine and oleic acid were chosen as substrates to design an optimal model reaction which will lead to high conversion rate utilizing lipase from Candida antacrctica (Novozyme 435) as biocatalyst in the organic solvent system. …”
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Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes by Reem Mustafa , Mah’d Al Debes

“…The proposed method achieves a 75% enhancement in energy efficiency compared to conventional Orthogonal Multiple Access (OMA) and an 11% improvement over benchmark NOMA algorithms. Additionally, it reduces outage probability by 25% and 10% relative to OMA and existing NOMA algorithms, respectively. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Hence, RX-STPM becomes an optimal equilibrium between exploration and exploitation strategies in leading the system towards global optima. …”
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Fuzzy-Genetic based approach in decision making for repair of turbochargers using additive manufacturing by Hiyam Adil Habeeb, Dzuraidah Abd Wahab, Abdul Hadi Azman, Mohd Rizal Alkahari

“…Genetic algorithm optimization method was used to optimize the cost of the repairing process once the decision on whether the turbocharger was repairable was determined by the Fuzzy system. …”
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Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies by Han B., Zahraoui Y., Mubin M., Mekhilef S., Seyedmahmoudian M., Stojcevski A.

“…In addition, the common objectives and constraints related to scheduling optimization are classified, and several optimization methods in the literature, including various intelligent algorithms, have been introduced, compared, and critically analyzed. …”

Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals by Ahmad, Farzana Kabir, Al-Qammaz, Abdullah Yousef Awwad, Yusof, Yuhanis

“…Regardless the popularity of EEG in recognizing human emotion, this study field is relatively challenging as EEG signal is nonlinear, involves myriad factors and chaotic in nature.These issues have led to high dimensional problem and poor classification results.To address such problems, this study has proposed a novel computational model, which consist of three main stages, namely a) feature extraction; b) feature selection and c) classifier. …”
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Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network by Al-Kharasani, Nori Mohammed Abdulkarem

“…The first objective to optimizing routing configuration parameter in different urban scenarios. The new framework model is introduced in order to provide a robust and reliable communication in VANETs, where the balance between the time needed to maintain the discovered routes and QoS requirements is necessary. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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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 quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). …”
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Protein Sequences Classification Using Modular RBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S., Hoogenraad, Nicholas J.

“…The connection weights between the final output layer and the transition output layer are optimized by delta rule, which serve as an integrator of the local neural classifiers. …”
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems by Ravari, Arastoo Rostami

“…The model can be applied to evaluate smart antenna systems and beamforming algorithms in the uplink by generating uncorrelated multipaths Rayleigh fading waveforms with certain spatio-temporal correlation and spatial coordinates relative to base stations to simulate received signals from mobiles and interferers. …”
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A swarm-based artificial immune system for solving multimodal functions by Yap D.F.W., Koh S.P., Tiong S.K., Prajindra S.K.

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Energy-efficient base station transmission design for green 5G massive MIMO and hybrid networks by Khodamoradi, Vahid

“…The proposed algorithm maximizes the EE by jointly optimizing the minimum data rate requirement, the number of BS antennas and users. …”
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Development and characterization of parenteral nano-delivery system loaded with azithromycin by Daood, Ghaidaa S

“…Kinetically, AZO release profile from nanoemulsion system in vitro appeared to fit best with the Higuchi model. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

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