Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

Get full text

Response Modeling and Optimization of Process Parameters in Turning Medium Carbon Steel Under Minimum Quantity Lubrication (MQL) with Vegetable Oil and Oil Blends by Indranil Das, Prianka Binte Zaman

“…Machining is an important aspect of manufacturing. …”
Get full text

On the Optimization of T6 Heat Treatment Parameters of a Secondary Al-Si-Cu-Mg Foundry Aluminum Alloy: A Microstructural and Mechanical Characterization by Mattia Merlin, Lorenzo Antonioli, Federico Bin, Cindy Morales, Chiara Soffritti

“…This study focuses on the optimization of the solution heat treatment parameters within the T6 heat treatment of an innovative AlSi7Cu0.5Mg0.3 secondary alloy, aiming at achieving energy savings and reducing the environmental impact related to the production of foundry components for the automotive industry. …”
Get full text

Parâmetros relevantes na determinação da velocidade terminal de frutos de café Important parameters for determination of terminal velocity of coffee fruits by Sandra M. Couto, Anderson C. Magalhães, Daniel M. de Queiroz, Itaciane T. Bastos

“…<br>The knowledge of the terminal velocity of a product is of fundamental importance in the development of separation machines using airflows. The behavior of the values of the terminal velocity of coffee fruits (varieties Catuaí and Hybrid Timor) was investigated in this work as a function of following parameters: (a) maturation level of the coffee at the harvesting ("green" and "cherry" fruits); (b) harvesting time; (c) variety; (d) moisture content of the fruits and (e) number of fruits in the sample used for the determinations of the terminal velocity. …”
Get full text

Review on System Identification, Control, and Optimization Based on Artificial Intelligence by Pan Yu, Hui Wan, Bozhi Zhang, Qiang Wu, Bohao Zhao, Chen Xu, Shangbin Yang

Get full text

Experimental Study on the Optimization of Rust Removal Effect on Surface Erosion of Grade A Marine Steel by Ultra-High-Pressure Water Jet by Qingbo Zhang, Yupeng Cao, Weidong Shi, Rui Zhou, Shuming Cheng, Zhengang Wang

“…Compared with the existing jet machining technology, the optimal process parameters obtained in this paper take into account both the rust removal quality and rust removal efficiency, and they improve the rust removal effect.…”
Get full text

The development of bionic trends in agricultural mechanics by L. F. Babitskiy, V. Y. Moskalevich, I. V. Sobolevsky

Subjects: Get full text

Analisis Sentimen terhadap Kebijakan Kuliah Daring Selama Pandemi Menggunakan Pendekatan Lexicon Based Features dan Support Vector Machine by Natasya Eldha Oktaviana, Yuita Arum Sari, Indriati Indriati

“…Sentiment analysis is useful for determining the timeliness of system computing in discussions on Twitter regarding online learning policies that tend to have negative or positive sentiments using the Support Vector Machine and Lexicon Based Features methods. The use of Lexicon Based Features affects the object of research which produces an accuracy value of 0.6, a precision value of 0.56, a recall value of 0.75, and a size of 0.64 with the optimal parameter in achieving convergence, namely (Lambda) = 0.7, the parameter value (gamma) = 0.0001, the parameter value (Complexity) = 0.0001, iterations = 50, and (Epsilon) = 0.00000001. …”
Get full text

Activation energy and Coriolis force impact on three-dimensional dusty nanofluid flow containing gyrotactic microorganisms: Machine learning and numerical approach by Jakeer Shaik, Reddy Seethi Reddy Reddisekhar, Thameem Basha Hayath, Cho Jaehyuk, Sathishkumar Veerappampalayam Easwaramoorthy

“…In recent times, machine learning methods have become powerful tools for solving complex problems, optimizing processes, and extracting insights from large datasets, especially in fluid dynamics. …”
Get full text

Method and Experimental Research of Transmission Line Tower Grounding Body Condition Assessment Based on Multi-Parameter Time-Domain Pulsed Eddy Current Characteristic Signal Extra... by Yun Zuo, Jie Wang, Xiaoju Huang, Yuan Liu, Zhiwu Zeng, Ruiqing Xu, Yawen Chen, Kui Liu, Hongkang You, Jingang Wang

“…Subsequently, DTCSV and TTS were used as inputs to a support vector machine (SVM) to classify the corrosion of the grounding body. …”
Get full text

Glaucoma Diagnostic Accuracy of Machine Learning Classifiers Using Retinal Nerve Fiber Layer and Optic Nerve Data from SD-OCT by Kleyton Arlindo Barella, Vital Paulino Costa, Vanessa Gonçalves Vidotti, Fabrício Reis Silva, Marcelo Dias, Edson Satoshi Gomi

“…To investigate the diagnostic accuracy of machine learning classifiers (MLCs) using retinal nerve fiber layer (RNFL) and optic nerve (ON) parameters obtained with spectral domain optical coherence tomography (SD-OCT). …”
Get full text

INOVASI TEKNOLOGI MACHINE LEARNING BAGI MASYARAKAT DI EKOWISATA SUNGKAI GREEN PARK NAGARI LAMBUNG BUKIT KECAMATAN PAUH PADANG by Maidi Rizki, Zaini Zaini, Muhammad Aditya Nikhaldo, Tesya Uldira Septiyeni, Teddy Yuliswar

“…Output dari matriks berupa parameter mean, skewness, kurtosis, entropy, contrast, dan energy. …”
Get full text

Analysis of the Topographical, Microstructural and Mechanical Surface Properties of Powder Bed Fusion Melted AlSi10Mg for a Broad Range of Process Parameters by Urban Klanjšček, Mitjan Kalin

“…Our study looks at the systematic variation of two key AM parameters over their full range using a commercial AM machine. …”
Get full text

A novel hybrid methodology for wind speed and solar irradiance forecasting based on improved whale optimized regularized extreme learning machine by S. Syama, J. Ramprabhakar, R Anand, V. P. Meena, Josep M. Guerrero

“…Then, a unique swarm intelligence technique, the non-linear dimension learning Hunting Whale Optimization Algorithm (NDLHWOA), is devised to optimize regularized extreme learning machine model parameters to capture the implicit information of each reconstructed sub-series. …”
Get full text

A FUZZY LOGIC MODEL FOR HUMAN DISTRESS DETECTION by DIMPLE OGUNBIYI, IBRAHIM OGUNDOYIN, CALEB AKANBI

“…Parameters to describe physically triggered distress were identified and used as input to the designed fuzzy model. …”
Get full text

Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models by Hongxia Ma, Jiandong Liu, Jia Zhang, Jiandong Huang

“…To estimate the compressive strength of cement-based materials with mining waste, the dataset based on a series of experimental studies was constructed. The support vector machine (SVM), decision tree (DT), and random forest (RF) models were developed and compared. …”
Get full text

New Method for High Water Pressure Tunnel Design Based on Machine Learning for Smart Grid Energy Management and Groundwater Environmental Balance by Xiaoming You, Gongxing Yan, Zhengqiang Yang

“…According to the fault characteristics and the section structure law, the section performance evaluation index is proposed, and the control parameter recommendations are given based on the test results. …”
Get full text

Improving the streamflow prediction accuracy in sparse data regions: a fresh perspective on integrated hydrological-hydrodynamic and hybrid machine learning models by Saeed Khorram, Nima Jehbez

“…This requires the ADPSO algorithm for parameter calibration, which elongates the computation time. …”
Get full text

Design and Testing of a Low-Speed, High-Frequency Straw Chopping and Returning Machine Using a Constant Breath Cam Mechanism by Han Lin, Jin He, Guangyuan Zhong, Hanyu Yang

Get full text

Optimizing solar collector efficiency and safety: A comparative thermal analysis of non-toxic hybrid nanofluid mixtures using machine learning by Mohib Hussain, Meraj Ali Khan, Hassan Waqas, Qasem M. Al-Mdallal

“…The effect of non-Fourier heat flux on the Blasius–Rayleigh–Stokes variable (BSRV) flow of a hybrid nano-fluid across a plate is investigated numerically for this purpose. Hyper-parameter optimization is performed for four alternative AI training methods to determine the best suitable choice. …”
Get full text