An Adaptive Signal Denoising Method Based on Reweighted SVD for the Fault Diagnosis of Rolling Bearings by Baoxiang Wang, Chuancang Ding

“…Due to the harsh and complex operating conditions, rolling element bearings (REBs) are prone to failures, which can result in significant economic losses and catastrophic breakdowns. …”
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Elite leader dwarf mongoose optimization algorithm by Anping Lin, Yong Liao, Chengfeng Peng, Xiang Li, Xing Zhang

“…Abstract Dwarf mongoose optimization algorithm (DMOA) is a recently proposed meta-heuristics, it attracts widely attention due to its effectiveness in solving complex optimization. However, DMOA utilizes roulette wheel selection to evolve the individual, this method may cause the swarm evolving unevenly and the swarm diversity losing rapidly. …”
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Prediction of Enthalpy of Mixing of Binary Alloys Based on Machine Learning and CALPHAD Assessments by Shuangying Huang, Guangyu Wang, Zhanmin Cao

“…This work offers an accelerated method for predicting complex multi-component system thermodynamics. Future research will focus on collecting more high-quality data to enhance model accuracy and generalization.…”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”
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Strategizing AI in Healthcare: A Multidimensional Blueprint for Transformative Decision-Making in Clinical Settings by Simon Martina, Kamin Stefan, Hamper Andreas, Wittenberg Thomas, Schmitt-Rüth Stephanie

“…By creating a comprehensive categorization system, we attempt to navigate the complex array of possible AI applications within the field of healthcare, hence enabling the identification, selection, and advancement of AIdriven initiatives. …”
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NORMALISATION OF THE DRIVE PRECISION OF METAL-CUTTING MACHINES by Irina A. Klenova, Dmitry A. Rudikov, Svetlana N. Kholodova

“…Conclusion The use of the proposed methodology expands the scientific basis for the development of algorithms and programs facilitating the selection of the optimal number of gear teeth for multiplying groups and structures and guaranteeing high accuracy of the gained series.…”
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The evolving role of programming and LLMs in the development of self-driving laboratories by John R. Kitchin

“…Machine learning and automation are transforming scientific research, yet the implementation of self-driving laboratories (SDLs) remains costly and complex, and it remains difficult to learn how to use these facilities. …”
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Diagnostics of the enterprise’s business potential by A.A.

“…The grouping of diagnostic methods was carried out in accordance with the goals of the diagnosis (diagnostics of the strategic perspective of development; diagnostics of competitiveness; diagnostics of the components of business potential; diagnostics of the possibility of the onset of a financial crisis), which contributes to increasing the efficiency of its implementation. It has been proven that achieving the goal and solving the tasks of diagnosing business potential is possible due to: the formation of reliable information support; successful selection of diagnostic methods; analytical substantiation of the conclusion regarding the state and opportunities of business potential; development and implementation of measures to improve the existing situation; conducting control over the implementation of measures.…”
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Neuro-Evolution of Augmenting Topologies for Dynamic Scheduling of Flexible Job Shop Problem by Jian Huang, Yarong Chen, Jabir Mumtaz, Liuyan Zhong

“…The NEAT algorithm harnesses the features of dynamic flexible job shop scheduling problems (DFJSPs) to devise heuristic rules for job selection and machine allocation, synthesizing these rules into coherent scheduling strategies. …”
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Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

“…This algorithm’s strong feature selection and clustering help target educational interventions by revealing student learning behaviors. …”
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Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…We demonstrate that the design of efficient neural network architectures is essential for soil moisture inversion, and provides valuable insights for deep learning applications in hydrological parameter estimation and other challenges in complex environmental contexts.…”
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Determination of Tungsten, Molybdenum and 5 Associated Elements in Tungsten-Molybdenum Ore by Inductively Coupled Plasma-Optical Emission Spectrometry with Direct Sintering by Zhou SONG, Yiping JI, Weihua WANG, Shaomin FANG, Jie YANG, Huoyan LUO, Yuqi ZHOU

“…BACKGROUNDTungsten-molybdenum ore is generally composed of a variety of minerals with complex composition. It is insoluble in hydrochloric acid, nitric acid and aqua regia, and the alkali melting and mixed acid dissolution method was often selected for sample digestion. …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

“…In the problem of anchor bolt (cable) stress prediction in coal mine roadways, model training often involves complex optimization tasks such as hyperparameter tuning and learning rate selection. …”
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Autonomous scheduling mechanism based on energy awareness for improving resource allocation in serverless IoT edge by Mohsen Ghorbian, Mostafa Ghobaei-Arani, Leila Esmaeili

“…This choice is complex since allocating the necessary resources to process requests depends on the energy available in the active nodes. …”
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Structural Optimization-Based Enhancement of the Dynamic Performance for Horizontal Axis Wind Turbine Blade by Ahmed Zarzoor, Alaa Jaber, Ahmed Shandookh

“…This research aims to improve the efficiency and power of wind turbine blades in order to enhance the efficiency and power of the devices. …”
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Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation by Srishti Gaur, Guler Aslan-Sungur (Rojda), Andy VanLoocke, Darren T. Drewry

“…Data-driven models have the potential to address these issues by offering flexible predictor selection and more efficient utilization of the information in predictor sets. …”
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Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System. by Vessela Krasteva, Irena Jekova, Remo Leber, Ramun Schmid, Roger Abächerli

“…Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a predominant normal (reference) beat template. …”
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Research on Underwater Sensor Network Adaptive Clustering Algorithm for Marine Environment Monitoring by Libin Xue, Chunjie Cao, Rongxin Zhu

“…This demonstrates that the algorithm can achieve efficient energy utilization and notably enhance network performance.…”
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Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. …”
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Multi-Domain Controversial Text Detection Based on a Machine Learning and Deep Learning Stacked Ensemble by Jiadi Liu, Zhuodong Liu, Qiaoqi Li, Weihao Kong, Xiangyu Li

“…Firstly, considering the multidimensional complexity of textual features, we integrate comprehensive feature engineering, i.e., encompassing word frequency, statistical metrics, sentiment analysis, and comment tree structure features, as well as advanced feature selection methodologies, particularly lassonet, i.e., a neural network with feature sparsity, to effectively address dimensionality challenges while enhancing model interpretability and computational efficiency. …”
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