A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…However, the efficiency of these applications depends on optimizing video compression parameters to maintain high detection accuracy while minimizing bandwidth usage and computational costs. …”
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Incremental GA-Based 3D Trajectory Optimization for Powered Parachute Aerial Delivery Systems by Hanafy M. Omar, Ayman Hamdy Kassem

“…A six-degrees-of-freedom (6-DOF) dynamic model of the PPC is developed, complemented by a novel optimization technique called Incremented Genetic Algorithms (IGA). …”
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Optimizing resource allocation in remote healthcare via blockchain-enabled decentralized networks and spectral clustering by A. Kanimozhi, K. Vidya

“…The proposed system utilizes the InterPlanetary File System (IPFS) to handle resource requests transparently and securely, while spectral and agglomerative clustering algorithms are employed to optimize delivery routes. …”
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Combined Use of Spectral and Structural Features for Improved Early Detection of Pine Shoot Beetle Attacks in Yunnan Pines by Yujie Liu, Youqing Luo, Run Yu, Lili Ren, Qi Jiang, Shaoshun He, Xinqiang Chen, Guangzhao Yang

“…In conclusion, this study identified optimal spectral and structural variables for UAV monitoring and improved HRS model accuracy and thereby provided technical support for the IPM of PSB outbreaks.…”
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Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…Traditional optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, have demonstrated adaptability in node placement but struggle with real-time self-learning capabilities, requiring frequent retraining to handle continuously changing conditions. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Meta-heuristic algorithms offer an alternative to traditional gradient-based optimizers for improving DNNs performance. …”
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Secrecy-Constrained UAV-Mounted RIS-Assisted ISAC Networks: Position Optimization and Power Beamforming by Weichao Yang, Yajing Wang, Dawei Wang, Yixin He, Li Li

“…To address this non-convex, multivariate, and coupled problem, we decompose it into three subproblems, which are solved iteratively using particle swarm optimization (PSO), semi-definite relaxation (SDR), majorization–minimization (MM), and alternating direction method of multipliers (ADMM) algorithms. …”
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Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain by Semra Tebrizcik, Süleyman Ersöz, Elvan Duman, Adnan Aktepe, Ahmet Kürşad Türker

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Development of a Smart Waste Management System for Route Optimization and Adaptive Demand Management in Dubai by H. Hassan, T. Ali, A. Tamimi

“…This paper presents an overview of the development of a Smart Waste Management System (SWMS) that integrates Geographic Information System (GIS) technology with waste route optimization algorithms and adaptive demand management strategies. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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Process parameter optimization for minimizing overcut in abrasive waterjet deep hole drilling of SS 316L by J. Bharani Chandar, N. Lenin, Alagar Karthick, Pradeep Kumar Singh, M. Siva Kumar, Md Irfanul Haque Siddiqui, Intesaaf Ashraf, Saurav Dixit, Nikolai Ivanovich Vatin, Choon Kit Chan

“…Thereafter, the effectiveness of the suggested algorithm has been validated using quality measures, namely hyper-volume and spacing by comparing it to the approaches of whale optimization, harmony search, and multiverse optimization algorithms. …”
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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…We segment data from various sensors within the automatic dependent surveillance-broadcast system using a designed sliding window of equal time steps, inputting them into the feature extraction network to capture spatiotemporal features. The improved snow ablation optimizer algorithm optimizes hyperparameters of this network automatically, while the multi-head attention mechanism redistributes weighted features, integrating them into comprehensive features. …”
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A factor analysis based automatic optimization method of vibration sensor points for ship acoustic reconstruction by Linchang Ye, Yun Liu, Zongpeng Tong, Zhaowang Xia, Wenkun Fan, Chunyu Zhang, Junhua Guo, Jianping Shen

“…The results show that the automatic optimization algorithm can improve the reconstruction accuracy concerning the uniform distribution method. …”
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A Framework for Generating S-Box Circuits with Boyer–Peralta Algorithm-Based Heuristics, and Its Applications to AES, SNOW3G, and Saturnin by Yongjin Jeon, Seungjun Baek, Giyoon Kim, Jongsung Kim

“…The gate count in the cipher and the circuit depth must be low to minimize these two metrics. Many optimization strategies have been developed for the linear layer, led by the Boyer–Peralta (BP) algorithm. …”
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Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method by Teng Jing, Yu Yang, Weimin Ru

“…Specifically, it achieved a rise time of 0.0049 s, a settling time of 0.0079 s, and a steady-state error of 0.0013 mm. The improved PSO algorithm ensures system stability while delivering faster dynamic response and superior control accuracy.…”
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Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization. by Ihab Hashem, Viviane De Buck, Seppe Seghers, Jan Van Impe

“…Our approach is inspired by how plants efficiently explore physical space in search of light energy, balancing exploration and exploitation while minimizing biomass cost. The algorithm navigates the objective space without revisiting previously explored areas by solving intermediate SOOPs visualized as branches within this space. …”
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Dual-Closed-Loop Control System for Polysilicon Reduction Furnace Power Supply Based on Hysteresis PID and Predictive Control by Shihao Li, Tiejun Zeng, Shan Jian, Guiping Cui, Ziwen Che, Genghong Lin, Zeyu Yan

“…Meanwhile, the outer loop employs a hybrid MFAC-based improved PID algorithm to optimize the temperature tracking performance, achieving precise temperature control even in the presence of system uncertainties. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…We construct a communication model for this scenario and propose an improved Dual-Actor Network Softmax Twin Delayed Deep Deterministic Policy Gradient algorithm based on deep reinforcement learning. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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