Integration of artificial intelligence and advanced optimization techniques for continuous gas lift under restricted gas supply: A case study by Leila Zeinolabedini, Forough Ameli, Abdolhossein Hemmati-Sarapardeh

“…To optimize the selected input variables, including tubing inside diameter, gas injection rate, and separator pressure, various optimization algorithms such as particle swarm optimization (PSO), ant colony optimization (ACO), genetic algorithm (GA), and a Novel optimization algorithm in a gas-lift study called grey wolf optimization (GWO), were utilized considering the constraint of the limited available gas. …”
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Energy-Saving Metro Train Timetable Optimization Method Based on a Dynamic Passenger Flow Distribution by Jingshuang Li, Fuquan Pan, Hailiang Tang, Sen Tong, Lixia Zhang, Xinguang Li, Xiaoxia Yang

“…A particle swarm optimization and genetic algorithm (PSO-GA) structure is designed to solve the model. …”
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Advancing Horticultural Crop Loss Reduction Through Robotic and AI Technologies: Innovations, Applications, and Practical Implications by H. W. Gammanpila, M. A. Nethmini Sashika, S. V. G. N. Priyadarshani

“…Tobal and Mokthar in 2014 pioneered an AI-assisted image processing method for weed identification, introducing an evolutionary ANN to optimize neural parameters using a genetic algorithm. However, the implementation of these technologies face challenges such as high initial costs, the need for technical expertise, and the integration of various data sources. …”
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Genetic Fuzzy System untuk Klasifikasi Tutupan Lahan Berdasarkan Foto Udara Unmanned Aerial Vehicle (UAV) by Budi Darma Setiawan, Alfi Nur Rusydi

“…The genetic fuzzy system is a classification method using a fuzzy system whose membership function is optimized using a genetic algorithm. The process consists of two stages, namely the training process, to find good fuzzy rules, and then proceed with tuning processes, namely the process of shifting the value constraints on the membership function of the fuzzy set used. …”
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Research on leakage and diffusion behavior of hydrogen doped natural gas in integrated pipeline corridors based on data drive by Xiaolong Gong, Hua Li, Cheng Li, Mingyue Kou, Lingxu Kong, Hongcheng Liu

“…In addition, the backpropagation neural network (BPNN) combined with the global optimization capability of genetic algorithm and the nonlinear mapping capability of neural network is used in this paper to provide a reliable technical means for the accurate prediction of explosion risk volume, which has important application value in the safety design of pipeline corridor and accident prevention and control. …”
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Klasifikasi Kebutuhan Jumlah Produk Makanan Customer Menggunakan K-Means Clustering dengan Optimasi Pusat Awal Cluster Algoritma Genetika by Yudi Istianto, Shofwatul 'Uyun

“…This study tries to apply data mining to classify the number of customer needs for food products using k-means clustering with optimization initial cluster center genetic algorithm. In this study used 210 data from product sales for three weeks. …”
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Analisis Metode Estimasi Biaya pada Perangkat Lunak Beserta Faktor-Faktor yang Mempengaruhi : A Systematic Literature Review by Amelia Devi Putri Ariyanto, Lutfiyatul ‘Azizah, Umi Laili Yuhana

“…Besides, this study also succeeded in finding the best method and combination of methods based on best accuracy, namely COCOMO II and the combination of Genetic Algorithm and Artificial Bee Colony, along with the five main factors that influence cost estimation so that it can be used by researchers or other practitioners to develop cost estimates for software projects. …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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Implementasi Algoritma Genetika dalam optimasi Performa Truk Sampah Menggunakan Aplikasi Trash Queen by Arief Kelik Nugroho, Muhammad Naufal Faza

“…Trash Queen utilizes genetic algorithm to run simulations repeatedly until an optimal solution is obtained. …”
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Monitoring the Concentrations of Na, Mg, Ca, Cu, Fe, and K in <i>Sargassum fusiforme</i> at Different Growth Stages by NIR Spectroscopy Coupled with Chemometrics by Sisi Wei, Jing Huang, Ying Niu, Haibin Tong, Laijin Su, Xu Zhang, Mingjiang Wu, Yue Yang

“…The effects of four spectral pretreatment methods and three wavelength selection methods, including the synergy interval partial least squares (SI-PLS) algorithm, genetic algorithm (GA), and competitive adaptive reweighted sampling method (CARS) on the model optimization, were evaluated. …”
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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

“…A key focus of this work is the combination of ML models with optimization algorithms like Genetic Algorithm, which improves the performance of ML models by optimizing hyperparameters and enhancing prediction accuracy. …”
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HHO–LSSVM prediction model of blast casting muck pile morphology based on Gaussian distribution by Ning MA, Li MA, Yinda LI, Tianxiang LI, Sen YANG, Fuming LIU, You ZHOU, Xiaomin WANG, Qifeng ZHANG, Mengbo LI

“…And the Gaussian distribution model combined with the HHO–LSSVM algorithm was used to predict the shape of the blast casting muck pile, compare the accuracy of the LSSVM, Particle Swarm Optimization (PSO) optimized Least Squares Support Vector Machine, and Genetic Algorithm (GA) optimized BP neural network models, at the same time, compare the predicted blast casting muck pile morphology with the actual blasting muck pile morphology. …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

“…The search for optimal parameters in the swarm model controller requires optimization techniques such as the genetic algorithm (GA) to direct the search for solutions that produce the best performance. …”
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Optimization of the Screw Conveyor Device Based on a GA-BP Neural Network by Qiang Guo, Yunpeng Zhuang, Houzhuo Xu, Wei Li, Haitao Li, Zhidong Wu

“…Via theoretical analysis, GA—BP (Genetic Algorithm—Back Propagation) simulation, and comparative experiments, the structural parameters and rotational speed of the spiral shaft in the screw conveying device are optimized. …”
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A Mixed Project-and-Stock Portfolio Optimization Model with Mean-SemiVariance-SemiEntropy Approach by Amirhosein Khayyatian, Majid Shakhsi-Niaei

“…Finally, the optimization problem has been solved using three metaheuristic algorithms: Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA), and Gray Wolfs Optimization (GWO).Findings: The results obtained by solving the model using the above-mentioned metaheuristic algorithms demonstrated that despite the high speed of the GWO algorithm, the solutions provided by the GWO algorithm were not satisfactory compared to the GA and ICA algorithms. …”
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