The Active and Reactive Power Generation Reduction Based on Optimal location of UPFC Based on Genetic Algorithm by Sana Khalid Abd Al Hassan, Firas Mohammed Tuaimah, Yasser Nadhum Abd, Ali Adil Al-Lami

“… The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. …”
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The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…It introduces a fusion of the African Vultures Optimization Algorithm (AVOA) and the Sand Cat Swarm Optimization (SCSO) with the Naïve Bayes (NB) model, aiming to elevate heating load prediction accuracy and streamline HVAC system optimization. …”
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VERIFICATION OF THE PARSEC METHOD AND OPTIMIZATION OF NACA-4412, SG-6043 USING GENETIC ALGORITHM IN MATLAB by Raheem Alhamdawee, M. Manzoor Hussain

“…The study also includes the improvement of the aerodynamic design of both airfoils through the use of a genetic algorithm which is coded and run in MATLAB, with the PARSEC parameters used as the base for optimization. …”
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Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225 by Karthikeyan M P

“…The precision of the stock market forecasts can be improved using metaheuristic algorithms such as the Moth-flame optimizer, which will provide the best optimization of the hyperparameters for an LSTM model. …”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

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Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector by G. G. Grebenuk, S. M. Nikishov, A. A. Krygin, L. A. Sereda

“…The most important results of the work performed are the following:• the methodology for forecasting the graph of the maximum totalpower consumption has been developed.• methods for optimizing energy consumption for each of the selected subsets of household appliances have been developed.• the optimization algorithms obtained have been simulated, which showed their operability, efficiency and the possibility of their practical application without any adaptation.Thus, the article proposes the solution of the problem of optimization of energy consumption in the housing sector, oriented to practical application.…”
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Feature Generation with Genetic Algorithms for Imagined Speech Electroencephalogram Signal Classification by Edgar Lara-Arellano, Andras Takacs, Saul Tovar-Arriaga, Juvenal Rodríguez-Reséndiz

“…The method leverages a genetic algorithm to create an optimal feature combination for the classification task and machine learning model. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…However, for treatment using neural networks based on improved Particle Swarm Optimization (PSO), known as PSONN, the accuracy and performance of current models must be improved. …”
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Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model by Mahir Mohammed Sharif Adam, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Samah Al Zanin

“…Finally, the parameter tuning of the fusion models is performed by using the Hiking Optimisation Algorithm (HOA) method. …”
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Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory by Ahmed M. Elshewey, Amira Hassan Abed, Doaa Sami Khafaga, Amel Ali Alhussan, Marwa M. Eid, El-Sayed M. El-kenawy

“…GGO algorithm’s binary format is specifically intended to choose the most effective set of features that can improve classification accuracy when compared to six other binary optimization algorithms. …”
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Hybrid Methods Random Forest and FOX-Inspired Optimization Algorithm for Selecting Features in Cervical Cancer Data by Afidatul Masbakhah, Umu Sa'adah, Mohamad Muslikh

“…In addition, other features such as First sexual intercourse, Number of sexual partners, age, and Hormonal Contraceptives also occupy the top five most influential features. Therefore, the hybrid RF-FOX method allows the performance of the model to be more optimized, thus helping in the identification of patients at risk of cervical cancer more precisely.…”
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Design of dual-layer heater based on genetic algorithm to optimize magnetic field gradient in vapor cell by Zhicheng Tan, Jing Zhu, Yanyan Liu, Siyang Lu, Lianqing Zhu

“…The study analyzed the influence of key parameters of the resistive wire, such as wire width, thickness, and spacing, on magnetic noise generation in the three-dimensional model of the heater. The parameter combinations were then optimized synchronously using genetic algorithms to reduce the magnetic field gradient in the vapor cell region and enhance the magnetic noise self-suppression capability of the heater. …”
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Classification Based on Brain Storm Optimization With Feature Selection by Yu Xue, Yan Zhao, Adam Slowik

“…Recently, some evolutionary algorithms (EAs) such as the fireworks algorithm (FWA) and brain storm optimization (BSO) algorithm have been employed to implement the evolutionary classification model and achieved the desired results. …”
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Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters by Hauwau Abdulrahman Aliyu, Ibrahim Olawale Muritala, Habeeb Bello-Salau, Salisu Mohammed, Adeiza James Onumanyi, Ore-Ofe Ajayi

“…Diabetes mellitus poses a global health concern, prompting the development of machine learning algorithms designed to construct a model for the accurate classification of patients, enabling precise diagnoses and early-stage treatment. …”
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Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Abstract The purpose of this study was to model and optimize the removal of methylene blue using a novel magnetic chitosan-carboxymethyl cellulose/multiwalled carbon nanotubes and to identify the most significant parameters influencing the adsorption efficiency. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…The results indicate that all three driving forces significantly enhance the overall level of urban-rural integration, with the most substantial improvements observed in economic and social integration. …”
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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…To optimize the performance of machine learning models, the paper incorporates genetic algorithms for hyperparameter optimization. …”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…Feature selection (FS) was conducted using Binary version of Grey Wolf Optimizer (BGWO), Particle Swarm Optimization (BPSO), Whale Optimization Algorithm (BWAO), and a novel hybrid BPSO-BWAO approach to identify the most relevant features for AQI prediction. …”
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The calculation algorithm of oil and gas production enterprise energy efficiency indicators by A. Yu. Arestova, V. N. Ulyanov, M. Yu. Frolov

“…It allows creating an optimal schedule of organizational and technical measures to regulate energy consumption and improve the energy efficiency of the enterprise.…”
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