An improved bistable stochastic resonance method and its application in early bearing fault diagnosis by Yonghui Zhao, Anqi Jiang, Wanlu Jiang, Enyu Tang, Xu Jiang, Xiaoyang Gu

“…Additionally, the cuckoo search (CS) algorithm is used to optimize the potential function parameters, enhancing fault diagnosis performance. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…The contribution in this paper proposes the following: the radial basis function (RBF) model will be enhanced by using two optimization algorithms, namely Horse Herd Optimization (HHO) and Wild Geese Algorithm (WGA). …”
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Acute severe ulcerative colitis: using JAK-STAT inhibitors for improved clinical outcomes by Shruthi Karthikeyan, Chetan Ambastha, Kian Keyashian

“…Here we discuss methods to optimize the dosing of IFX to maximize its efficacy, while exploring recent work done on the safety and efficacy of JAK-STAT inhibitors as a salvage therapy, therefore suggesting a novel treatment algorithm to improve clinical outcomes in medically managed ASUC patients.…”
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A location-constrained crowdsensing task allocation method for improving user satisfaction by Huihui Chen, Bin Guo, Zhiwen Yu, Liming Chen

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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Binary program taint analysis optimization method based on function summary by Pan YANG, Fei KANG, Hui SHU, Yuyao HUANG, Xiaoshao LYU

“…Taint analysis is a popular software analysis method, which has been widely used in the field of information security.Most of the existing binary program dynamic taint analysis frameworks use instruction-level instrumentation analysis methods, which usually generate huge performance overhead and reduce the program execution efficiency by several times or even dozens of times.This limits taint analysis technology’s wide usage in complex malicious samples and commercial software analysis.An optimization method of taint analysis based on function summary was proposed, to improve the efficiency of taint analysis, reduce the performance loss caused by instruction-level instrumentation analysis, and make taint analysis to be more widely used in software analysis.The taint analysis method based on function summary used function taint propagation rules instead of instruction taint propagation rules to reduce the number of data stream propagation analysis and effectively improve the efficiency of taint analysis.For function summary, the definition of function summary was proposed.And the summary generation algorithms of different function structures were studied.Inside the function, a path-sensitive analysis method was designed for acyclic structures.For cyclic structures, a finite iteration method was designed.Moreover, the two analysis methods were combined to solve the function summary generation of mixed structure functions.Based on this research, a general taint analysis framework called FSTaint was designed and implemented, consisting of a function summary generation module, a data flow recording module, and a taint analysis module.The efficiency of FSTaint was evaluated in the analysis of real APT malicious samples, where the taint analysis efficiency of FSTaint was found to be 7.75 times that of libdft, and the analysis efficiency was higher.In terms of accuracy, FSTaint has more accurate and complete propagation rules than libdft.…”
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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…On the other hand, the most widely used nature-inspired algorithms require large numbers of system simulations to yield a satisfactory design. …”
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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.…”
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Courier Assignment and Routing Problem Algorithm in Online Food Delivery System with Multi-Customer Delivery Patterns by Prita Meilanitasari, Maulin Masyito Putri, Ilda Auly Sita Agustin, Muhammad Faisal Ibrahim, Dwi Sekar Arumjani

“…After processing and analyzing the numerical data, the study identified the most effective scenario that led to improved delivery times and benefits for couriers, enabling them to manage more orders and achieve faster delivery compared to existing algorithms. …”
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Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems by Sung Soo Im, Do Guen Yoo, Joong Hoon Kim

“…Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmony memory considering rate. …”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

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Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment by Dimple Dimple, Jitendra Rajput, Nadhir Al-Ansari, Ahmed Elbeltagi

“…As a result, machine learning algorithms can improve irrigation water quality characteristics, which is critical for farmers and crop management in various irrigation procedures. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…Then, a convergence factor is introduced to balance the global and local search abilities of the whale algorithm to improve the convergence speed. The sample space is then iteratively searched using the improved whale algorithm. …”
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Dynamically Dimensioned Search Grey Wolf Optimizer Based on Positional Interaction Information by Fu Yan, Jianzhong Xu, Kumchol Yun

“…The comparison results for the 23 benchmark functions show that the proposed DGWO algorithm performs significantly better than the GWO and its improved variant for most benchmarks. …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
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A Wi-Fi RSS-RTT Indoor Positioning Model Based on Dynamic Model Switching Algorithm by Xu Feng, Khuong An Nguyen, Zhiyuan Luo

“…However, their performance varies significantly across different indoor environments, making it challenging to identify the most suitable system for all scenarios. To address this challenge, we propose an algorithm that dynamically selects the most optimal Wi-Fi positioning model for each location. …”
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Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

“…BoM is then used to select the optimal classification model from a set of candidates, to further improve the accuracy of diagnosis. …”
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Research on Quality Anomaly Recognition Method Based on Optimized Probabilistic Neural Network by Li-li Li, Kun Chen, Jian-min Gao, Hui Li

“…In order to eliminate the defect of experience value, the key parameter of PNN was optimized by the improved (SGA) single-target optimization genetic algorithm, which made PNN achieve a higher rate of recognition accuracy than PNN optimized by standard genetic algorithm. …”
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Kinematic Constrained RRT Algorithm with Post Waypoint Shift for the Shortest Path Planning of Wheeled Mobile Robots by Sisi Liu, Zhan Zhao, Jun Wei, Qianqian Zhou

“…Once the distance between the new node and the target is within a certain threshold, the tree growth stops and a target connection based on minimum turning radius arc is proposed to generate an initial complete random path. The most significant difference from traditional RRT-based methods is that the proposed method optimizes the path based on Dubins curves through a post waypoint shift after a random path is generated, rather than through parent node selection and rewiring during the exploring tree growth. …”
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