Pipeline corrosion rate prediction model using BP neural network based on improved sparrow search algorithm by Shuhui XIAO, Chuanjia DU, Chengjun WANG

“…Methods This paper proposes a pipeline corrosion rate prediction model using an optimized BP neural network based on an improved Sparrow Search Algorithm to address the aforementioned disadvantages. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm by Linfei Yin, Yongzi Ye, Xiaoping Xiong, Jiajia Chai, Hanzhong Cui, Haoyuan Li

“…In this study, MRDMGWOA is simulated on the IEEE 39 system and 118 system, and its performance is compared with other heuristic algorithms. The results show that: (1) in the IEEE 39 system, MRDMGWOA reduces the power generation cost and CO₂ emission by 17% and 22%, respectively, and reduces the computation time by 16.14 s compared with the centralized optimization; (2) in the IEEE 118 system, the two metrics are further optimized, with a 20% and 17% reduction in the cost and emission, respectively, and an improvement in the computational efficiency by 45.46 s; (3) in the spacing, hypervolume, and Euclidian metrics evaluation, MRDMGWOA outperforms other algorithms; (4) compared with the existing DMOGWO and DMOMFO, the computation time of MRDMGWOA is reduced by 177.49 s and 124.15 s, respectively, and the scheduling scheme obtained by MRDMGWOA is more optimal than DMOGWO and DMOMFO.…”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…Through a comprehensive evaluation of the running time results, the root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R2), a new algorithm, the grasshopper optimization algorithm (GOA), which is suitable for optimizing an ANN to predict PPV, is obtained. …”
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An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
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TOPSIS inspired cost-efficient concurrent workflow scheduling algorithm in cloud by K. Kalyan Chakravarthi, L. Shyamala, V. Vaidehi

“…Therefore, it is a great challenge to improve system performance and optimize several scheduling criteria simultaneously. …”
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Fast-Charging Optimization Method for Lithium-Ion Battery Packs Based on Deep Deterministic Policy Gradient Algorithm by Zhi Zhang, Taijun Guo, Yefeng Liu, Xinfu Pang, Zedong Zheng

“…First, a deep reinforcement learning charging optimization model is constructed, aiming to minimize charging time and SOC balancing cost, with constraints on battery voltage, temperature, SOC, and SOH. …”
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A Low-Carbon Scheduling Method for Container Intermodal Transport Using an Improved Grey Wolf–Harris Hawks Hybrid Algorithm by Meixian Jiang, Shuying Lv, Yuqiu Zhang, Fan Wu, Zhi Pei, Guanghua Wu

“…The model is solved using an improved grey wolf–Harris hawks hybrid algorithm (IGWOHHO). …”
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ＲGB-DSLAM Visual Odometry Optimization Algorithm by DONG Jing-wei, JIANG Yi-ming, HAN Zhi-yu

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Research on Cold Chain Logistics Joint Distribution Vehicle Routing Optimization Based on Uncertainty Entropy and Time-Varying Network by Huaixia Shi, Yu Hong, Qinglei Zhang, Jiyun Qin

“…The solution combines simulated annealing strategies with genetic algorithms. It also uses the entropy mechanism to optimize uncertainties, improving global search performance. …”
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Research on electric vehicle charging and discharging optimization scheduling strategy under V2G mode based on improved crisscross algorithm by MA Li, PENG Weilun, FAN Jinheng, ZHOU Zhiming

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Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
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An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty by Hachen Ali, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Seyedali Mirjalili

“…Furthermore, seven other algorithms (Dandelion Optimizer (DO), Grey wolf optimizer (GWO), The whale optimization algorithm (WOA), Artificial electric field algorithm (AEFA), Harris hawks optimization (HHO), Multi-verse optimizer (MVO) and Slime mould algorithm (SMA)) are used to compare the obtained solution from APO. …”
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Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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Road damage detection based on improved YOLO algorithm by Luyao Ma, Ming Chen

“…Experimental results show that compared to existing methods, this algorithm boosts the retrieval rate by 2.3%, increases the average value by 0.3, and improves the harmonic mean F1 by 0.7 relative to other models. …”
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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…To predict the VIV performance of a double-deck steel truss (DDST) girder with additional aerodynamic measures, the VIV response of a DDST bridge was investigated using wind tunnel tests and numerical simulation, a learning sample database was established with numerical simulation results, and a prediction model for the amplitude of the DDST girder and VIV parameters was established based on three machine learning algorithms. The optimization algorithm was selected using root mean square error (RMSE) and the coefficient of determination (R²) as evaluation indices and further improved with a genetic algorithm and particle swarm optimization. …”
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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids by Yuan Wang, Wangjia Lu, Wenjun Du, Changyin Dong

“…Background: To address the uncertainties of renewable energy power generation, the disorderly charging characteristics of electric vehicles, and the high electricity cost of the power grid in expressway service areas, a method of economic dispatch optimization based on the improved particle swarm optimization algorithm is proposed in this study. …”
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Improving frequency stability in grid-forming inverters with adaptive model predictive control and novel COA-jDE optimized reinforcement learning by Muhammad Zubair Yameen, Zhigang Lu, Fayez F. M. El-Sousy, Waqar Younis, Baqar Ali Zardari, Abdul Khalique Junejo

“…The offline phase employs a novel Hybrid Crayfish Optimization and Self-Adaptive Differential Evolution Algorithm (COA-jDE) to minimize the cost function $$U_{offline}$$ , deriving optimal control parameters (Q, R) before real-time deployment. …”
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