Multi-objective optimization placement strategy for SDN security controller considering Byzantine attributes by Tao WANG, Hongchang CHEN

“…By giving the software defined network distributed control plane Byzantine attributes, its security can be effectively improved.In the process of realizing Byzantine attributes, the number and location of controllers, and the connection relationship between switches and controllers can directly affect the key network performance.Therefore, a controller multi-objective optimization placement strategy for SDN security controllers considering Byzantine attributes was proposed.Firstly, a Byzantine controller placement problem (MOSBCPP) model that comprehensively considered interaction delay, synchronization delay, load difference and the number of controllers was constructed.Then, a solution algorithm based on NASG-II was designed for this model, which included the initialization function, the mutation function, the fast non-dominated sorting function and the elite strategy selection function.Simulation results show that this strategy can effectively reduce interaction delay, synchronization delay, load difference and the number of controllers, while improving control plane security.…”
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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

“…The K-fold cross-validation method with K=10 and hyperparameter tuning were applied to obtain the optimal performance of both models. The results showed that SVM without undersampling achieved 92% accuracy, while with undersampling the accuracy decreased to 76%. …”
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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

“…Experimental results demonstrate a marked improvement in product yield and process stability while reducing manufacturing costs. …”
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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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UCA-YOLOv8n: a real-time and efficient fruit chunks detection algorithm for meal-assistance robot by Fei Liu, Mingyue Hu

“…Methods We propose an improved YOLOv8n algorithm optimized for real-time, high-accuracy fruit chunk detection. …”
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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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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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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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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 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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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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A comprehensive review of AI and machine learning techniques in antenna design optimization and measurement by Pradnya A. Gajbhiye, Satya P. Singh, Madan Kumar Sharma

“…This review examines the latest advancements in applying AI/ML approaches to antenna design optimization. It explores the use of various AI/ML algorithms such as neural networks, decision trees, genetic algorithms, and particle swarm optimization in this context. …”
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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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Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…OPA-APSO differs from most existing approaches as it considers the amount of energy harvested while optimizing the solution. Finally, simulation results demonstrate that OPA-APSO improves energy efficiency and throughput of the network significantly as compared to other existing techniques. …”
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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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