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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Speed control of wheeled mobile robot by nature-inspired social spider algorithm-based PID controller by Khan, Huma, Khatoon, Shahida, Gaur, Prerna, Abbas, Mohamed, Saleel, Chanduveetil Ahamed, Khan, Sher Afghan

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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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Algorithms based on spider daddy long legs for finding the optimal route in securing mobile ad hoc networks by Ghathwan, Khalil Ibrahim

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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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Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions by Yadav A., Pal N., Khan F.A., Parihar R.S., Khan A., Solanki S., Pansari D., Sharma P., Yadav K.

“…s superiority as compared to conventional control techniques under different operating conditions. ? The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.…”

A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

“…Emerging data science tools, particularly Machine Learning (ML) big data analytics, are being utilized to predict air pollution intensity and frequency under varying climatic conditions for effective mitigation plans. …”
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ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models by Ong, Song Quan, Nathan Pinoy, Lim, Min Hui, Kim Bjerge, Francisco Javier Peris-Felipo, Rob Lind, Jordan P. Cuff, Samantha M. Cook, Toke Thomas Høye

“…In this paper, we present a high-throughput scanner-based method for capturing images of arthropods that can be used to generate large datasets suitable for training machine learning algorithms for identification. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Economic dispatch with environmental consideration using Honey Bee algorithm / Zaidi Faiq Mohd Noh by Mohd Noh, Zaidi Faiq

“…Environmental concerns in industries shows increment in term of concerns and awareness among companies by strictest the pollutions regulation. This paper presents a Honey Bee (HB) Algorithm solution for Economic and Emission Dispatch problem in power system. …”
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Development Of Contrast Enhancement Algorithm For Images Captured Under Insufficient Illumination by Huang, Nan

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GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

“…Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). …”
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Solar maximum power point tracking based on improved incremental conductance algorithm by Mailah, Nashiren Farzilah, Boyao, Ma

“…Traditional maximum power point tracking (MPPT) algorithms, including incremental conductance (INC) and perturbation and observation (P&O), often get stuck in local optima under these conditions, while intelligent algorithms such as particle swarm optimization (PSO) are hampered by large oscillations and uncertain convergence. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter by Taghvaee, Mohammad Hossein

“…Simulation results are presented to validate performance of the algorithm under different irradiation schemes, and to compare with the results obtained from conventional algorithm. …”
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Predictive dynamic CFD approach to reducing airborne transmission in naturally ventilated hospital rooms: Impact of window opening angles during transitional cold seasons in China... by Haowei , Yu

“…Furthermore, the study found that if the window opening direction is improperly set, window-opening behavior may lead to severe pollutant dispersion rather than effectively reducing indoor pollutant levels. …”
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Optimal Power Flow Solution With Stochastic Renewable Energies Using Nature Inspired Algorithm by Abdul Mu’iz Zulfadli, Ab Wahab

“…By the end of this study, this algorithm should have been demonstrated to be a process that is simple to use and capable of searching for a nearglobal optimal solution with significant convergence and effectiveness when compared to other algorithms.…”
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Energy Management System For Controlling Series Hybrid Electric Motorcycle by Cham , Chin Long

“…They create enormous pollutants due to the lack of viable pollution prevention technologies. …”
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