Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

“…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
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An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms by Luc Eyembe Ihonock, Jean-François Dikoundou Essiben, Benjamin Salomon Diboma, Joe Suk Yong

“…The preprocessing stage of data is also included in the suggested technique, which starts with the design of the data-collecting device and ends with a hybrid model algorithm. Particle swarm optimization and artificial neural network methods are combined in the hybrid algorithm. …”
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Exploring Flexible Penalization of Bayesian Survival Analysis Using Beta Process Prior for Baseline Hazard by Kazeem A. Dauda, Ebenezer J. Adeniyi, Rasheed K. Lamidi, Olalekan T. Wahab

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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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Study on PID gain parameter optimization for a quadcopter under static wind turbulence using bio-inspired algorithms by Olukunle Kolawole Soyinka, Monica Ngunan Ikpaya, Lumi Luka

“…This study solves this problem using Bio-inspired algorithms to tune the controller gain. To determine the required PID controller gain parameters this paper utilizes a Simulink model of a quadcopter combined with the particle swarm optimization (PSO) algorithm and the cuckoo search algorithm (CSA) optimization respectively to minimize error in the attitude rate. …”
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Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
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Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks by Nadia Shamshad, Lei Wang, Kiran Saleem, Danish Sarwr, Salil Bharany, Ahmad Almogren, Jaeyoung Choi, Ateeq Ur Rehman, Ayman Altameem

“…Results demonstrate notable improvements in localization accuracy by optimizing the localization error rate from 4.59m to $$3.88 \times 10^{-8}$$ m, Reducing localization energy consumption rate 0.0045J in addition for the first time we have also computed the localization Time cost rate which is 0.06762s. we assumed that in real-time and in NS-3 simulations on the Aqua-sim model indicate communication speed at 1500m/s. …”
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Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
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Path planning in radioactive environment of nuclear facilities based on modified A-star algorithm and search neighborhood optimization by Biao Zhang, Xingfu Cai, Guoqiang Li, Xiaomeng Li, Minjun Peng, Haowei Wang

“…Compared with the Probabilistic Roadmap Method (PRM), PRM has the shortest computation time due to its random sampling characteristics, but the cumulative dose and path length are higher than the two A-star algorithms. For models of varying complexity, optimizing the number of search neighborhoods further enhances search efficiency without affecting path planning results. …”
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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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Advanced hybrid computational analysis of febuxostat solubility using machine learning in supercritical processing method by Turki Al Hagbani, Rami M. Alzhrani, Majed Ahmed Algarni

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Optimized memory allocation in edge-PLCs using Deep Q-Networks and bidirectional LSTM with Quantum Genetic Algorithm by N. Naveen Kumar, S. Saravana, S. Balamurugan, P. Seshu Kumar, S. Suresh

“…By leveraging principles of quantum computing, this optimization algorithm explores the solution space more efficiently, allowing for faster convergence and improved performance. …”
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Optimal control of asynchronous drive of auxiliary machines of electric rolling stock by Yu. M. Kulinich, S. A. Shukharev, V. K. Dukhovnikov, D. A. Starodubtsev

“…The proposed system of optimal control of electric locomotive auxiliary machines is designed to improve the energy efficiency of the drive with a new algorithm for selecting the optimal value of the rotor flux linkage by reducing the current consumed by the drive. …”
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Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
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Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems by Hongwei Cheng, Jun Li, Xiaoming Zhang, Tingjuan Li, Panpan Zhang

“…It outperforms other state-of-the-art optimization algorithms, demonstrating significant improvements in global optimization, solution accuracy, and convergence speed. …”
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ML-based approach to potato diseases diagnosis using image processing and whale optimization algorithm for feature selection by Zhongxu Li, Seyed Mohamad Javidan

“…Nature-inspired feature extraction techniques, such as the Whale Optimization Algorithm (WOA), have gained considerable attention recently. …”
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IoT driven healthcare monitoring with evolutionary optimization and game theory by Shitharth Selvarajan, Hariprasath Manoharan, Taher Al-Shehari, Nasser A. Alsadhan, Subav Singh

“…The model is validated through four case studies, demonstrating an average improvement of 60% over existing methodologies. …”
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Optimization design on process parameters of copper wire bonding for power modules by HU Biao, CHENG Lanxian, LI Zhenling, DAI Xiaoping

“…In order to improve the copper wire bonding performance of the power modules, an optimization design scheme of process parameters for copper wire bonding was proposed by using the six-factor five-level orthogonal test method, and combining the back propagation (BP) neural network and genetic algorithm (GA). …”
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Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system by Li Xin, Li Yuesong

“…According to the key frames saved in the previous steps, feature points in local maps, sensor information, and loop information, a global optimization algorithm based on graph optimization model is constructed to optimize the position and pose of intelligent hardware system and the position of spatial feature points. …”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

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