Application of Deep Learning for Stock Prediction Within the Framework of Portfolio Optimization in Quantitative Trading by Xiaoyu Qin

“… This paper proposes a method for stock prediction and portfolio optimization as a part of quantitative trading based on a combination of Bi-RNN and a modified snake optimization algorithm (MSOA) to build optimal portfolios and outperform conventional models and benchmarks. …”
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Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

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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

“…The enhanced version of the Custom-CNN-CBAM model utilizing the BEO, referred to as Custom-CNN-CBAM-BEO, demonstrated superior convergence speed and accuracy compared to models optimized with genetic algorithm (GA) and particle swarm optimization (PSO), highlighting the effectiveness of the BEO optimization approach. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
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Analysis of Smart Grid Optimal Scheduling considering the Demand Response of Different EV Owners by Xiaohua Zhang, Chongyang Liao, Xingrui Chen, Kuiheng Deng, Bolin Chen, Yibo Gong

“…According to charging and vehicle-to-grid (V2G) data of EV owners, the K-means clustering algorithm (K-means) is used to classify EV owners, and the demand response (DR) model is established based on the classification results. …”
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A Day-Ahead Optimal Battery Scheduling Considering the Grid Stability of Distribution Feeders by Umme Mumtahina, Sanath Alahakoon, Peter Wolfs

“…This study presents a comprehensive framework for optimizing energy management systems by integrating advanced methodologies for weather forecasting, energy cost analysis, and grid stability using a mixed-integer linear programming (MILP) algorithm. …”
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Bayesian Optimized GridDehazeNet for Adaptive Haze Removal in Real-World Applications by Sungkwan Youm

“…By employing our algorithm, we effectively identify the best architectural parameters, achieving higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) compared to models without this optimization. …”
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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 study of parameter aggregation algorithms for virtual power plant terminal decentralized resource scheduling characteristics in alpine regions by Yan Wang, Ruizhi Zhang, Ying Wang, Wen Xiang, Lu Wang

“…This approach enhances scheduling flexibility and resolves the grid-side secondary dispatch issue. An improved ant colony algorithm based on continuous optimization was used to solve the aggregation parameters. …”
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Optimized deep residual networks for early detection of myocardial infarction from ECG signals by Pon Bharathi A, Madavan R, Sakthivel E

“…The proposed system introduces a novel MI detection technique using a Deep Residual Network (DRN), where the solution is optimized by the proposed Social Ski-Spider (SSS) Optimization algorithm is the novel combination of both Social Ski-driver (SSD) Optimization and the Spider Monkey Optimization (SMO). …”
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Numerical Simulation Study on Adjoint-Based Optimization of a Propeller Using Reverse Engineering by Hao Wang, Yaoqing Liao, Mingge Shen, Sujie Zhou, Gang Xu

“…The optimization target was set at a 10% improvement in the lift-to-drag ratio, and the adjoint-based optimization of the target airfoil sections at different angles of attack was performed using the gradient descent algorithm. …”
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Reverse Logistics Network Optimization for Retired BIPV Panels in Smart City Energy Systems by Cimeng Zhou, Shilong Li

“…Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. …”
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Optimizing sum rates in IoT networks: A novel IRS-NOMA cooperative system by Mukkara Prasanna Kumar, Ammar Summaq, Sunil Chinnadurai, Poongundran Selvaprabhu, Vinoth Babu Kumaravelu, Md. Abdul Latif Sarker, Dong Seog Han

“…By leveraging our optimization algorithm, the proposed system ensures efficient resource allocation, achieving superior spectral efficiency and fairness among users compared to traditional models. …”
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Enhanced medical image segmentation using novel level set evolution and efficient optimization by Samad Wali, Adil Jhangeer, Ariana Abdul Rahimzai, Samina Samina, Mudassar Imran

“…Unlike prior edge-based algorithms, which frequently fail with noisy images and have large computing costs, our method incorporates an improved edge indicator term into the level set architecture, considerably improving performance on degraded images. …”
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Optimization of the Canopy Three-Dimensional Reconstruction Method for Intercropped Soybeans and Early Yield Prediction by Xiuni Li, Menggen Chen, Shuyuan He, Xiangyao Xu, Panxia Shao, Yahan Su, Lingxiao He, Jia Qiao, Mei Xu, Yao Zhao, Wenyu Yang, Wouter H. Maes, Weiguo Liu

“…With these improvements, a high-precision 3D canopy point-cloud model of soybeans covering the entire growth period was successfully constructed. …”
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Optimal Allocation of SVG Considering Voltage Mitigation of DG Grid-connected Inverter and APF by Jing XU, Shuya TIAN, Tiejun ZHAO, Xiaogang GAO, Ju YE, Lingyan BU, Wenmiao LIU

“…A multi-objective SVG optimal allocation model is established with minimum total cost of SVG and optimal mitigation effect of system voltage deviation, and the improved genetic algorithm is used to solve the allocation model. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
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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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Adaptive Optimization and Dynamic Representation Method for Asynchronous Data Based on Regional Correlation Degree by Sichao Tang, Yuchen Zhao, Hengyi Lv, Ming Sun, Yang Feng, Zeshu Zhang

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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

“…Microarray data are high dimensional, which can degrade the performance of the ML-based models. For this, feature selection becomes essential.MethodsSwarm Optimization Algorithm (SSA), Improved Maximum Relevance and Minimum Redundancy (IMRMR), and Boruta form the basis of this work’s ML-based model BIMSSA. …”
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