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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The optimization model of building construction based on BIM and improved NSGA-III algorithm by Meng Wang

“…Therefore, a multi-objective optimization model was constructed based on building information management technology, and an improved non-dominated sorting genetic algorithm III was introduced to optimize the model solution. …”
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Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization by Chen Fei, Zhuo Lu, Weiwei Jiang, Liang Zhao, Fan Zhang

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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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An Improved Squirrel Search Algorithm for Optimization by Tongyi Zheng, Weili Luo

“…Squirrel search algorithm (SSA) is a new biological-inspired optimization algorithm, which has been proved to be more effective for solving unimodal, multimodal, and multidimensional optimization problems. …”
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CMACGSA: Improved Gravitational Search Algorithm Based on Cerebellar Model Articulation Controller for Optimization by Nazmiye Ebru Bulut, Emre Dandil, Ugur Yuzgec, Alpaslan Duysak

“…Recent advances in the field often involve hybrid methods that combine several algorithms to improve performance. This study introduces an improved Gravitational Search Algorithm, named CMACGSA, which incorporates the Cerebellar Model Articulation Controller (CMAC)-a neural network model-to enhance the performance of Gravitational Search Algorithm (GSA). …”
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Optimization Performance and Efficiency Improvement of Microgrid Scheduling Model by Honggang JIA, Zhuding WANG, Yuanyuan YUE, Huan YAN, Na YAN, Qiangfei CAO

“…First of all, considering the cost of electricity charges, the cost of energy storage regulation, the user’s inappropriate cost and the benefit of response subsidies, an optimization model with the goal of minimizing the daily comprehensive power consumption cost is established; Then, aiming at the problem that the global optimization ability of the standard differential evolution algorithm is insufficient and the solution efficiency needs to be improved, the scaling factor and crossover operator are optimized and improved to form an adaptive hybrid differential evolution algorithm; Finally, taking the micro grid system as an example, the operation optimization of energy storage and demand response and the comparative analysis of calculation examples are carried out.The results show that the proposed method is suitable for multi scenario computing and has high optimization performance and solving efficiency.…”
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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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An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection by Congxiao Jiang, Lingang Yang, Yuqing Gao, Jie Zhao, Wenne Hou, Fangmin Xu

“…We propose a novel Sea Wind-Aware Improved A*-Guided Genetic Algorithm (SWA-IAGA), which integrates an improved A* algorithm to guide the genetic algorithm for efficient path planning, with the assistance of relevant graphical knowledge. …”
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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

“…In this paper, an enhanced assistive Technology for Blind People through Object Detection Using a Hiking optimization algorithm (EATBP-ODHOA) technique is proposed. …”
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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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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

“…The model employs a random forest algorithm integrated with a multi-task learning strategy and utilizes a particle swarm optimization (PSO) algorithm to optimize fracturing parameters. …”
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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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A Novel Black Widow Optimization Algorithm Based on Lagrange Interpolation Operator for ResNet18 by Peiyang Wei, Can Hu, Jingyi Hu, Zhibin Li, Wen Qin, Jianhong Gan, Tinghui Chen, Hongping Shu, Mingsheng Shang

“…In an attempt to surmount this challenge, evolutionary computation algorithms can automatically adjust the hyper-parameter learning rate to improve training efficiency and model performance. …”
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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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