A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots by Anis Naema Atiyah Rafai, Noraziah Adzhar, Nor Izzati Jaini

“…This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

“…However, performance varied with KNN, Naive Bayes, and Decision Tree, highlighting the importance of tailored approaches for optimal classification accuracy. Further optimization and experimentation are crucial for improving algorithm performance in real-world applications of brain tumor classification. …”
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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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A Data-Driven Parameter Adaptive Clustering Algorithm Based on Density Peak by Tao Du, Shouning Qu, Qin Wang

“…Clustering is an important unsupervised machine learning method which can efficiently partition points without training data set. However, most of the existing clustering algorithms need to set parameters artificially, and the results of clustering are much influenced by these parameters, so optimizing clustering parameters is a key factor of improving clustering performance. …”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. These algorithms include Pearson correlation, hierarchical clustering, and decision tree (DT) models. …”
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OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS by O. S. Khalyutina

“…In this case, if the output signal of the compensating effects should coincide with the ideal signal at the most.…”
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Algorithms for big data mining of hub patent transactions based on decision trees by Zhukov Aleksandr, Pronichkin Sergey, Mihaylov Yuri, Kartsan Igor

“…Based on evolutionary computing, the optimal values of the parameters of algorithms for big data mining of hub patent transactions have been established.…”
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Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks by Jingjing Ma, Jie Liu, Wenping Ma, Maoguo Gong, Licheng Jiao

“…In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. …”
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Optimizing the Performance of Data Warehouse by Query Cache Mechanism by Ch Anwar Ul Hassan, Muhammad Hammad, Mueen Uddin, Jawaid Iqbal, Jawad Sahi, Saddam Hussain, Syed Sajid Ullah

“…In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. …”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Among the models, the XGBoost algorithm demonstrated the highest performance, providing precise predictions that closely aligned with the actual groundwater levels. …”
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Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

“…With the goal of reducing task offloading delay and improving enhanced reaction time, a VANET-based task scheduling system is proposed after selecting an optimal route in the VANET. …”
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A nonrevisiting genetic algorithm based on multi-region guided search strategy by Qijun Wang, Chunxin Sang, Haiping Ma, Chao Wang

“…This study proposes a nonrevisiting genetic algorithm with a multi-region guided search to improve the search efficiency. …”
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Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
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Application of the YOLOv11-seg algorithm for AI-based landslide detection and recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

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Optimizing Locations of Primary Schools in Rural Areas of China by Yulong Chen

“…Scientific location selection of schools is an important way to optimize the allocation of educational resources, improve the efficiency of operating schools, and realize the balanced development of education, especially in rural areas. …”
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Task-dependent Optimal Weight Combinations for Static Embeddings by Nathaniel Robinson, Nathaniel Carlson, David Mortensen, Elizabeth Vargas, Thomas Fackrell, Nancy Fulda

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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…The results confirm that the method significantly reduces the bit error rate by 3.3% and improves the success rate of deframing in most experimental wells. …”
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Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…Finally，the initial Kriging model is updated with MP （minimizing the predicted objective function） infill-sampling criterion and genetic algorithm，and the optimal design is obtained via the final Kriging model. …”
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