APPA: An adaptation path planning algorithm for real-time obstacle avoidance in multi-robot systems by Jianzhi Jin, Mou Wu, Ping Fan, Guonian Jin

“…APPA attains a 35% reduction in average pathfinding time compared to PRIMAL.…”
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Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

“…GWO plays a vital role in weight optimization, enabling the reduction of weights in models that are particularly sensitive to noise. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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Physical and AI-Based Algorithms for Retrieving Cloud Liquid Water and Total Precipitable Water from Microwave Observation by Wenxiang Chen, Yang Han, Fuzhong Weng, Hao Hu, Jun Yang

“…The integration of physical and AI-based algorithms enables the retrieval of CLW and TPW directly from FY-3F satellite observations. …”
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A multi-algorithm prognostic model combining inflammatory indices and surgical features in distal cholangiocarcinoma by Yi Yin, Yi Yin, Luyuan Bai, Xinyue Mu, Xinyue Mu, Shan Zhang, Panpan Zhai, Panpan Zhai

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Explainable machine learning for predicting lung metastasis of colorectal cancer by Zhentian Guo, Zongming Zhang, Limin Liu, Yue Zhao, Zhuo Liu, Chong Zhang, Hui Qi, Jinqiu Feng, Peijie Yao

“…The Random Forest (RF) algorithm demonstrated the highest predictive capability within the internal test set (AUC of 0.980, AUPR of 0.941). …”
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A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

“…[Conclusion] (1) The combined prediction model established based on LSTM and PSO algorithms effectively extracts nonlinear characteristics between environmental variables and effect variables, leading to improved prediction performance. (2) The PSO-LSTM prediction model demonstrates good versatility. …”
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Prediction of coalbed methane productivity based on neural network models by JIN Yi, ZHENG Chenhui, SONG Huibo, MA Jiaheng, YANG Yunhang, LIU Shunxi, ZHANG Kun, NI Xiaoming

“…Finally， according to the classification results， combined with the actual drainage data， the BP and LSTM neural network algorithms were used to predict the daily gas production of CBM wells.ResultsThe results show that： （1） Based on the grey correlation method model analysis， 10 parameters such as permeability， gas saturation and reservoir pressure gradient in the study area are the key factors affecting the gas production performance of coalbed methane； （2） Using fuzzy mathematics evaluation method to evaluate the enrichment of coalbed methane， the gas production effects of 34 wells in the study area is divided into three categories： favorable area， relatively favorable area and unfavorable area. （3）A coal reservoir daily gas production prediction model was established based on the LSTM algorithm， with a prediction error value between 4.06% and 14.79%， and the average error value of 11.09%. …”
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Development and Validation of Predictive Models for Non-Adherence to Antihypertensive Medication by Cristian Daniel Marineci, Andrei Valeanu, Cornel Chiriță, Simona Negreș, Claudiu Stoicescu, Valentin Chioncel

“…Five machine learning models were developed to predict non-adherence, defined by ARMS quartile-based thresholds. …”
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Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. …”
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Optimizing capacitor bank placement in distribution networks using a multi-objective particle swarm optimization approach for energy efficiency and cost reduction by Mehrdad Ahmadi Kamarposhti, Raymond Ghandour, Mahmoud Abdel-Aty, Mohamed Hafez, Mohanad Alfiras, Shawkat Alkhazaleh, Ilhami Colak, Ahmed Solyman

“…The novelty of this work lies in the application of the MOPSO algorithm to optimize capacitor bank placement, considering multiple objectives such as energy loss reduction, voltage stability, and cost savings, which differentiates it from conventional approaches. …”
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A Beyond 5G OTFS Waveform Radio for Smart Hospital: PAPR Reduction in OTFS Using the Cuckoo Search–Based PTS Method by Arun Kumar, Aziz Nanthaamornphong

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Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

“…Experimental results demonstrate a 28.7% reduction in road network traffic variance (from 42,760 to 32,100), 22.4% improvement in public transit path redundancy, and 30.4–44.6% decrease in regional traffic load variance with minimal costs. …”
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Nonlinear Compensation of Multi-CAP VLC System Employing Clustering Algorithm Based Perception Decision by Xingyu Lu, Kaihui Wang, Liang Qiao, Wen Zhou, Yiguang Wang, Nan Chi

“…The CAPD method can outperform the Volterra series based nonlinear equalizer with a lower BER value (at least 10% reduction) and relatively lower complexity. To the best of our knowledge, this is the first time that the clustering algorithm in machine learning is successfully applied to VLC systems.…”
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Proposing a flood management solution based on optimal usage allocation via genetic algorithm by Davood Mokhtari, Aliakbar Rasouli, Monire Moosabeigi

“…Conclusion: The results and achievements of this study include proposing a land use optimization model based on a multi-objective genetic algorithm for flood reduction, integrated river basin management, as well as programming in an expansive form to use in future studies.…”
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Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review by Shaina Mackin, Vincent J. Major, Rumi Chunara, Remle Newton-Dame

“…Abstract Background AI and predictive analytics have increased the speed of innovation in medicine. …”
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Research on Universal Time/Length of Day Combination Algorithm Based on Effective Angular Momentum Dataset by Xishun Li, Yuanwei Wu, Dang Yao, Jia Liu, Kai Nan, Zewen Zhang, Weilong Wang, Xuchong Duan, Langming Ma, Haiyan Yang, Haihua Qiao, Xuhai Yang, Xiaohui Li, Shougang Zhang

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Optimal Design of Linear Quadratic Regulator for Vehicle Suspension System Based on Bacterial Memetic Algorithm by Bala Abdullahi Magaji, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…BMA combines the bacterial foraging optimization algorithm (BFOA) and the memetic algorithm (MA) to enhance the effectiveness of its search process. …”
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Research on 3D stability algorithm of potential sliding body in surface mining in confined space by Dong WANG, Xiaoyu XING, Li YIN, Shougong WANG, Lingwei KONG, Xiangyu MENG

“…In the actual design of deep coal mining step, the slope stability decreases with the continuous reduction of +843 plate width. When the local slope angle is 25.58°, it just meets the requirement of safety reserve factor 1.2. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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