Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…The LSTM component forecasts power generation rates based on environmental conditions, while the EO component optimizes the LSTM model's hyper-parameters through training. …”
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Urban Multi-Scenario Land Use Optimization Simulation Considering Local Climate Zones by Jie Chen, Zikun Dong, Ruijie Shi, Geng Sun, Ya Guo, Zhuopeng Peng, Min Deng, Kaiqi Chen

“…The research employs a genetic algorithm to optimize the LCZ quantity structure in order to improve the urban temperature environment. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. To reduce complexity, only two tuning screws are considered in the optimization. …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…Early diagnosis is essential to reduce mortality and improve patients' quality of life. This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process by Wen-Chin Chen, An-Xuan Ngo, Jun-Fu Zhong

“…The system integrates advanced optimization techniques, including the Taguchi method, analysis of variance (ANOVA), back-propagation neural network (BPNN), and a hybrid particle swarm optimization–genetic algorithm (PSO-GA) approach to identify optimal process parameters. …”
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An Optimized Cascaded CNN Approach for Feature Extraction From Brain MRIs for Tumor Classification by Santosh Kumar Chhotray, Debahuti Mishra, Sarada Prasanna Pati, Sashikala Mishra

“…Four pre-trained models—VGG16, ResNet50, NASNet, and DenseNet121—capture distinct features, and a Custom-CNN integrates these models with the convolutional block attention module (CBAM). The bald eagle optimization (BEO) algorithm is used to optimize the hyperparameters while balancing exploration and exploitation. …”
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Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

“…The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). …”
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Seasonal optimization of solar PV tilt angles for enhanced energy efficiency in Rajasthan, India by Saaransh Choudhary, Shiv Lal, Sumit Verma

“…For this purpose, a general algorithm for the optimization of the solar tilt angle is investigated based on MATLAB software for four different locations in Rajasthan, India. …”
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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…Abstract Spontaneous Intracerebral Hemorrhage (SICH) is a critical condition with high mortality rates, requiring prompt and effective prognostic assessment. This study aims to improve SICH outcome prediction by developing the Alpha Evolution Moss Growth Optimization (AEMGO) algorithm for feature selection in high-dimensional medical datasets. …”
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Optimization of Communication Signal Adversarial Examples by Selectively Preserving Low-Frequency Components of Perturbations by Yi Zhang, Lulu Wang, Xiaolei Wang, Dianxi Shi, Jiajun Bai

“…As a result, selectively preserving LFCP is established as the fundamental concept of the optimization strategy. By utilizing the binary search algorithm, which considers the inconsistency in the model’s predictions as a constraint, LFCP can be effectively identified, and the aim of minimizing perturbed distortion while maintaining ASR can be achieved. …”
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Prediction and Optimization for Multi-Product Marketing Resource Allocation in Cross-Border E-Commerce by Yi Xie, Heng-Qing Ye, Wenbin Zhu

“…In the second stage, the resource allocation problem is formulated as a large-scale integer programming model, which is then transformed into a minimum-cost flow problem to ensure computational efficiency while preserving solution optimality. Experiments on real-world data show that our framework significantly outperforms baseline strategies, achieving a 14.48% increase in order volume and revenue improvements ranging from 0.19% to 43.91%. …”
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Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation by Ankit Garg, K. R. Niazi, Shubham Tiwari, Sachin Sharma, Tanuj Rawat

“…The optimization model is solved using the Modified Water Evaporation algorithm. …”
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A Servo Control Algorithm Based on an Explicit Model Predictive Control and Extended State Observer with a Differential Compensator by Zhuobo Dong, Shuai Chen, Zheng Sun, Benyi Tang, Wenjun Wang

“…By employing an offline optimization approach, a control law is explicitly formulated to handle system constraints while minimizing online computational overhead. …”
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Research on the optimization model of anti-breast cancer candidate drugs based on machine learning by Zhou Dong, Hong Chen, Yuchen Yang, Hairong Hao

“…Additionally, a multi-model fusion strategy and Particle Swarm Optimization (PSO) algorithm were employed to optimize both biological activity and ADMET properties, thereby improving the prediction of Caco-2, CYP3A4, hERG, HOB, and MN properties. …”
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A Hierarchical Evolutionary Search Framework with Manifold Learning for Powertrain Optimization of Flying Vehicles by Chenghao Lyu, Nuo Lei, Chaoyi Chen, Hao Zhang

“…The co-optimization aims to minimize fuel consumption, battery state-of-health (SOH) degradation, and manufacturing costs while satisfying dynamic and energy management constraints. …”
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PSA-Optimized Compressor Speed Control Strategy of Electric Vehicle Thermal Management Systems by Kun Xia, Lianglu Yu, Jingxia Wang, Wei Yu

“…Precise control of compressor speed, informed by real-time sensor data, is essential for improving TMS efficiency and extending EV range. This study proposes a control strategy based on the PID Search Algorithm (PSA), ensuring optimal thermal management for an integrated battery and cabin TMS. …”
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A power-distribution joint optimization arrangement for multi-point source jamming system by Zhihao Cai, Shiqi Xing, Sinong Quan, Xinyuan Su, Junpeng Wang

“…Third, a multi-objective time-varying mapping particle swarm optimization (MOTPSO) algorithm is adopted to solve the model, thereby achieving the optimal arrangement. …”
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Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
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Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels by Yi-bing Li, Xue-ying Diao, Qian-hui Dong

“…Rank minimization rate maximization aims to reduce the impact of interference on undesired users as much as possible while improving the desired data rate. Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. …”
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Optimization of multioutlet hydrant location and pressurized irrigation network layout using the GRASP metaheuristic by César González-Pavón, Carmen Virginia Palau, Juan Manzano-Juárez, Santiago Guillem-Picó, Ibán Balbastre-Peralta

“…To address this, the study proposes an optimization approach utilizing geographic information systems (GIS) and the greedy randomized adaptive search procedures (GRASP) algorithm. …”
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