Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method by Yueqi LIU, Lei HOU, Shuaishuai TANG, Huai SU, Xingtao LI

“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.,Particle Swarm Optimization) that overlook constraints during iterative updates,this research proposed a novel Exterior Penalty Function Method for optimizing gas supply reliability.This method transformed constraints in the allocation model into penalty function terms,established a revised objective function,and converted the constrained allocation problem into an unconstrained extremum problem.Applying this method to a practical pipeline system,optimal gas supply reliability allocation values were derived.The results demonstrate that the Exterior Penalty Function Method significantly reduces computational time without compromising accuracy.The allocation outcomes exhibit robust convergence and align with engineering practicality.By clarifying the optimized allocation values of unit gas supply reliability and comparing them with the current reliability,the weak units in the gas supply system can be identified,providing a scientific basis for improving the gas supply reliability of pipeline systems.…”
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A Convolution Auto-Encoders Network for Aero-Engine Hot Jet FT-IR Spectrum Feature Extraction and Classification by Shuhan Du, Wei Han, Zhenping Kang, Yurong Liao, Zhaoming Li

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Thermal Conductivity Characteristics of Thermal Insulation Materials Immersed in Water for Cold-Region Tunnels by Youyun Li, Yongmei Sun, Yuan Zhuang, LiMin Duan, Ke Xie

“…The correlation between gray volume moisture content and mass moisture content is determined by comparing different algorithms of gray volume moisture content and volume moisture content. …”
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Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation by Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao

“…Experimental evaluations on the large-scale IP102 pest dataset demonstrate that the proposed ARD method consistently outperforms existing state-of-the-art algorithms across various class-incremental learning scenarios, significantly narrowing the performance gap compared to fully trained models.…”
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A Custom Reinforcement Learning Environment for Hybrid Renewable Energy Systems: Design and Implementation by Dalton F. Guedes Filho, Marcelo A. Moret, Erick G. Sperandio Nascimento

“…We present HybridEnergyEnv, an open-source, Gym-style simulation environment designed for reinforcement learning (RL) research in hybrid renewable energy systems (HRES) combining wind, solar, and battery storage. …”
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Harvester Maintenance Prediction Tool: Machine Learning Model Based on Mechanical Features by Rodrigo Oliveira Almeida, Richardson Barbosa Gomes da Silva, Danilo Simões

“…In default mode, we ran 25 popular algorithms through the database and compared them based on accuracy and error metrics. …”
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Water quality prediction using LSTM with combined normalizer for efficient water management by N. Mahesh, J. Jagan Babu, K. Nithya, S.A. Arunmozhi

“…Nevertheless, conventional water quality prediction models mostly use data-driven approaches and only depend on diverse sensor data. In recent research, deep learning algorithms have been extensively used for water quality prediction due to their robust ability to map highly nonlinear connections while maintaining acceptable computational efficiency. …”
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MW-UNet: Multi-Scale Weighted Connection UNet for Identification and Classification of Non-Meteorological Clutter over Big Radar Data by Mengmeng Cui, Chen Zeng, Xiaolong Xu, Muhammad Bilal, Xiaoyu Xia

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Energy Efficiency Optimization in Swarm Robotics for Smart Photovoltaic Monitoring by Dimitris Ziouzios, Nikolaos Baras, Minas Dasygenis, Vayos Karayannis, Constantinos Tsanaktsidis

“…The proposed approach merges advanced swarm robotics algorithms with energy-efficient methods to reduce power consumption while still ensuring effective coverage. …”
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Landslide vulnerability mapping using GIS-based statistical model for sustainable ecosystem management in the Himalayan region of Teesta River basin, India by Subodh Chandra Pal, Tanmoy Biswas, Sumit Ghorai, Chaitanya Baliram Pande, Aznarul Islam, Abu Reza Md. Towfiqul Islam, Edris Alam

“…The landslide inventory data are subdivided into training data sets (70%) for applying algorithms in models and testing data sets (30%) for testing model accuracy. …”
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From Simulation to Implementation: A Systems Model for Electric Bus Fleet Deployment in Metropolitan Areas by Ludger Heide, Shuyao Guo, Dietmar Göhlich

“…Current electrification research often addresses individual components—energy consumption, scheduling, or charging infrastructure—in isolation, lacking integrated frameworks that capture complex system interactions. …”
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Empowering Optimal Operations with Renewable Energy Solutions for Grid Connected Merredin WA Mining Sector by Md Ohirul Qays, Ravi Kumar, Minhaz Ahmed, Stefan Lachowicz, Uzma Amin

“…The optimization method also resulted in the lowest computation time of 1.153 s and highest accuracy 99.247% when compared with other existing algorithms. Furthermore, the integration of renewable energy (RE) technologies within mining operations substantially reduces carbon emissions by 67%, thus contributing to broader global sustainability purposes. …”
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ARGContextProfiler: extracting and scoring the genomic contexts of antibiotic resistance genes using assembly graphs by Nazifa Ahmed Moumi, Shafayat Ahmed, Connor Brown, Amy Pruden, Liqing Zhang

“…Testing on real, synthetic, and semi-synthetic data, including long-read sequencing data from environmental samples, demonstrated that ARGContextProfiler offers superior accuracy, precision, and sensitivity compared to conventional assembly-based methods. ARGContextProfiler thus provides a powerful tool for uncovering the genomic context of ARGs in metagenomic sequencing data, which can be of value to both fundamental and applied research aimed at understanding and stemming the spread of AR. …”
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Docking Methods for Robot-assisted Rhytidectomy and Platysmaplasty by Anastasiya S. Borisenko, MD, PhD, Valentin I. Sharobaro, MD, PhD, Alexey E. Avdeev, MD, PhD, Yousif M. Ahmed Alsheikh, MD

“…There are no docking algorithms or methods for plastic surgery operations, especially those involving the head and neck area. …”
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Cereal and Rapeseed Yield Forecast in Poland at Regional Level Using Machine Learning and Classical Statistical Models by Edyta Okupska, Dariusz Gozdowski, Rafał Pudełko, Elżbieta Wójcik-Gront

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Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…This article reviews current challenges and examines proposed solutions, with a focus on precision fertilization enabled by advanced technologies such as geographic information systems, global positioning systems, the internet of things, artificial intelligence and machine learning algorithms, and unmanned aerial and ground vehicles for fertilizer management. …”
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Delineating flood susceptibility zones using novel ensemble models – An application of evidential belief function, relative frequency ratio, and Shannon entropy by Samuel Yaw Danso, Yi Ma, Isaac Yeboah Addo

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FedDL: personalized federated deep learning for enhanced detection and classification of diabetic retinopathy by Dasari Bhulakshmi, Dharmendra Singh Rajput

“…The results indicate that implementing these algorithms in an FL environment significantly enhances privacy and performance compared to conventional centralized learning methods.…”
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Development of data driven machine learning models for the prediction and design of pyrimidine corrosion inhibitors by Aeshah H. Alamri, N. Alhazmi

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Predicting Coronavirus Pandemic in Real-Time Using Machine Learning and Big Data Streaming System by Xiongwei Zhang, Hager Saleh, Eman M. G. Younis, Radhya Sahal, Abdelmgeid A. Ali

“…Then, five regular machine learning algorithms were performed and compared: decision tree, logistic regression, k-nearest neighbors, random forest, and support vector machine to select the best model for the online prediction component. …”
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