Machine learning-aided lattice optimization for ultra-lightweight 3D-printed aligners by Poom Narongdej, Bradley Yuhasz, Tianmin Kong, Diego Rojas, Qidi Peng, Ehsan Barjasteh

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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…This study developed an advanced bankruptcy prediction model using Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN) algorithms based on datasets from the UCI machine learning repository. …”
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PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses by Xiaoyong Liu, Hui Fu

“…Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM), particle swarm optimization (PSO), and cuckoo search (CS). …”
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Surface topography creation of machine elements after carburizing process with application of burnishing method by Lidia Gałda

“…Particles circulating in various types of machine kinematic pairs contribute to accelerated or even emergency wear of the equipment. …”
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A vibration signal processing method based on SE-PSO-VMD for ultrasonic machining by Honghuan Chen

“…Ultrasonic Machining (USM) has broad applicability in numerous industrial fields. …”
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STUDY ON TUBE SHELL TRANSVERSE DISPLACEMENTS UNDER ITS MACHINING BASED ON COMPUTER SIMULATION by Bogdan Igorevich Golub

“…The possibility to increase parameter accuracy (pitch of thread, pressure angle, external and internal thread diam eter) for various kinds of thread on the seamless casing is studied. …”
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An open-source tool for analysis and automatic identification of dendritic spines using machine learning. by Michael S Smirnov, Tavita R Garrett, Ryohei Yasuda

“…Our software relies on a machine learning approach to minimize any need for parameter tuning from the user. …”
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The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

“…By making use of the improved Particle Swarm Optimization algorithm to optimize the parameters of Support Vector Machine, it is applied to the complex industrial system of penicillin fermentation. …”
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Characterization of the Machine Behavior During Hollow Embossing Rolling of Metallic Bipolar Half Plates by Martin Wagner, Mohaned Alaluss, Robin Kurth, Robert Tehel, Franz Reuther, Steffen Ihlenfeldt

“…In this paper, the elastic machine and forming roll behavior as a major influence parameter is described and analyzed on qualitative level and verified by simulation. …”
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Information-entropy-driven generation of material-agnostic datasets for machine-learning interatomic potentials by Aparna P. A. Subramanyam, Danny Perez

“…Abstract In contrast to their empirical counterparts, machine-learning interatomic potentials (MLIAPs) promise to deliver near-quantum accuracy over broad regions of configuration space. …”
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Extraction of Alteration Information from Hyperspectral Data Base on Kernel Extreme Learning Machine by Shuhan Yang, Shufang Tian

“…The ideal parameters of the Kernel Extreme Learning Machine model were successfully acquired by utilizing the sparrow optimization method for continuous search and iteration, avoiding the blindness and arbitrariness associated with parameter selection by humans. …”
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Efficiency-aware machine-learning driven design of solar harvester for renewable energy application by Abdullah Baz, Shobhit K. Patel

“…The optical response and parameter optimization analysis have been examined in this work in the wavelength range of 0.4 μm–1.6 μm. …”
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Stock Price Prediction Using Machine Learning: Evidence from Pakistan Stock Exchange by Zafar Akhter, Dr. Hassan Raza

“… This research investigates the utilization of machine learning methodologies for the purpose of forecasting the fluctuations in stock values inside the financial market. …”
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Applications of machine learning to high temperature and high pressure environments: A literature review by Hengkai Wang, Zengtao Lv, Santosh Kumar, Qinglin Wang

“…The rapid development of machine learning makes it a powerful tool to predict some parameter or mechanism of materials and brings a new chance to simulate more complex experimental environments. …”
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Evaluating Communication Performance in Rotating Electrical Machines Using RSSI Measurements and Artificial Intelligence by Sonia Ben Brahim, Samia Dardouri, Hanen Lajnef, Amel Ben Slimane, Ridha Bouallegue, Tan-Hoa Vuong

“…This paper introduces a novel methodology for evaluating communication performance in rotating electric machines using Received Signal Strength Indication (RSSI) measurements coupled with artificial intelligence. …”
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Computational models based on machine learning and validation for predicting ionic liquids viscosity in mixtures by Bader Huwaimel, Jowaher Alanazi, Muteb Alanazi, Tareq Nafea Alharby, Farhan Alshammari

“…This study assesses three influential machine learning algorithms that are based on the Decision Tree methodology. …”
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Cache Contention Aware Virtual Machine Placement and Mitigation Using Adaptive ABC Algorithm by Bharati Ainapure, Nishu Gupta, Mohammad Derawi

“…Cache contention in cloud computing can degrade system performance and lead to security vulnerabilities like side-channel attacks. Virtual Machine (VM) migration is a practical solution to mitigate cache contention by relocating affected VMs to optimal Physical Machines (PMs). …”
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Flood prediction in urban areas based on machine learning considering the statistical characteristics of rainfall by Se-Dong Jang, Jae-Hwan Yoo, Yeon-Su Lee, Byunghyun Kim

“…Traditional numerical models for flood prediction are accurate but time-consuming due to extensive parameter calibration and data processing. This study addresses these limitations by proposing a machine learning-based flood prediction method using a Random Forest model. …”
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A Parts Detection Network for Switch Machine Parts in Complex Rail Transit Scenarios by Jiu Yong, Jianwu Dang, Wenxuan Deng

“…This article proposes a complex scene rail transit switch machine parts detection network YOLO-SMPDNet (YOLO-based Switch Machine Parts Detecting Network). …”
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Evaluation of Several Machine Learning Models for Field Canal Improvement Project Cost Prediction by Saadi Shartooh Sharqi, Aayush Bhattarai

“…Project cost is a highly sensitive component to diverse parameters and hence it is associated with complex trends that make it difficult to be predicted and fully understood. …”
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