A multi-objective metaheuristic method for node placement in dynamic IoT environments by Farzad Kiani

“…Abstract This study introduces an optimal Node Placement based on Enhanced Sand Cat Swarm Optimization (NP-ESCSO) algorithm, a novel metaheuristic approach for solving the node placement problem in dynamic IoT environments. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source by P. Sundararaman, E. Mohan, S. V. Aswin Kumer, Sridhar Udayakumar, Abdissa Fekadu Moti

“…The proposed BAT algorithm gives the optimal locations to place the required amount of DG sources to improve the stability and minimize the power losses and maintain the voltage profile of the systems. …”
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Anomaly Detection in Wireless Sensor Networks Using Immune-Based Bioinspired Mechanism by Ramsha Rizwan, Farrukh Aslam Khan, Haider Abbas, Sajjad Hussain Chauhdary

“…Several solutions have been proposed using Artificial Immune System (AIS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) algorithm, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and so forth. …”
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2HR-Net VSLAM: Robust visual SLAM based on dual high-reliability feature matching in dynamic environments. by Wang Yang, Huang Chao, Zhang Yi, Tan Shuyi

“…Finally, the shared matching Siamese network with a unique dual-branch feature fusion strategy and similarity optimization algorithm is proposed to enhance the accuracy of feature matching. …”
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Adaptive Multi-Sensor Fusion for SLAM: A Scan Context-Driven Approach by Yijing Zhang, Jia Liu, Runxi Cao, Yunxi Zhang

“…Experimental results on multiple public benchmark datasets demonstrate that in the case of almost the same computational efficiency, the proposed algorithm effectively enhances the accuracy of positioning, the robustness of the algorithm and accuracy of mapping, improving the global consistency of the generated map.…”
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Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification by Chunye Wu, Nan Wang, Yu Wang

“…This paper proposes a new strategy and algorithm based on a cost-sensitive support vector machine to improve the minority class recall rate to 1 because the misclassification of even a few samples can cause serious losses in some physical problems. …”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…The study utilized a substantial dataset with a total of 61,584 images, and the most effective model attained an impressive Root Mean Square Error (RMSE) of 0.81, underscoring the model's remarkable capacity to accurately detect and predict casting quality issues. …”
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Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…The simulator uses sampling-based path planning algorithms such as RRT*, Fast RRT*, RRT*-Smart, informed-RRT*, and Honey Bee Mating Optimization-based Fast-RRT*. …”
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Calcium and Vitamin D supplements in the treatment of osteoporosis. by Ahmed I Alobaidi, Ahmed Hazim Al Aoodh, Nabeel Yousif Abdullah, HUSHAM JASSIM, Mubder Abdul_Raheem Mohammed saeed, Housamaddeen Alfarhan

“…In addition to that we face a lot of osteoporotic fractures with catastrophic sequalae on personal and community levels that cause increased morbidity and mortality rate which cost billions of dollars each year. Prevention of this disorder is highly recommended to improve people’s health and to decrease financial burden upon the society. …”
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Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…Each model’s performance was assessed via measuring Root Mean Square Error (RMSE), R2, Mean Absolute Error (MAE), and Monte Carlo Cross-Validation (CV) scores using a Tabu Search method for optimization. …”
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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…Additionally, the use of the Single-Step Proximal Policy Optimization (SSPPO) algorithm enhances the exploration of nozzle geometries by maximizing aerodynamic performance while balancing computational efficiency. …”
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Application of GA in Furniture Modeling Style Design by Heng Yu, Chunjing Liu

“…In order to improve the production efficiency of furniture, it is necessary to optimize it. …”
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Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

“…The framework includes a decision support module that considers environmental, cost, and aesthetic aspects to identify the optimal layout. …”
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Rock Fracture Monitoring Based on High-Precision Microseismic Event Location Using 3D Multiscale Waveform Inversion by Yi Wang, Xueyi Shang, Kang Peng, Rui Gao

“…Based on this initial location, the multiscale waveform inversion strategy (from coarse to fine grids) and the L-BFGS iteration optimization algorithm were separately jointly selected to improve wavefield modeling speed efficiency and iterative convergence rate. …”
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Analysis and Research on Intelligent Logistics Data under Internet of Things and Blockchain by Yige Li

“…To explore the security performance of logistics data transmission in an Intelligent Logistics System (ILS) under the Internet of Things (IoT) and Blockchain (BC), IoT is introduced to optimize the logistics transportation process. First, BC is adopted to improve the ILS under IoT, and ILS under IoT combined with BC is established. …”
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Fault diagnosis model of rolling bearings based on the M-YOLO network by NING Shaohui, ZHANG Shaopeng, WU Yukun, DU Yue, FAN Xiaoning

“…ObjectiveThe algorithms developed for the combination of deep learning and bearing fault diagnosis have achieved initial results, but most of them are processed by processing one-dimensional vibration data and input into the network structure for diagnosis, while the research on fault diagnosis technology using two-dimensional signals as input is still on the surface, and the analysis of such methods is rarely reported. …”
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Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment by Yong Wang, Xiuwen Wang, Xiangyang Guan, Jinjun Tang

“…In comparison with NSGA algorithm, the NSGA-II algorithm incorporates an elitist strategy, which can improve the computational speed and robustness. …”
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Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The feature-section algorithm based on the combination of genetic algorithm and information theory (GAITH) was used to select the most important input combinations and introduce them into the prediction models. …”
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Dynamic-budget superpixel active learning for semantic segmentation by Yuemin Wang, Ian Stavness

“…A static budget could result in over- or under-labeling images as the number of high-impact regions in each image can vary.MethodsIn this paper, we present a novel dynamic-budget superpixel querying strategy that can query the optimal numbers of high-uncertainty superpixels in an image to improve the querying efficiency of regional active learning algorithms designed for semantic segmentation.ResultsFor two distinct datasets, we show that by allowing a dynamic budget for each image, the active learning algorithm is more effective compared to static-budget querying at the same low total labeling budget. …”
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