Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks by Naveen GARG, Siddharth DHRUW, Laghu GANDHI

“…The paper presents the application of Artificial Neural Networks (ANN) in predicting sound insulation through multi-layered sandwich gypsum partition panels. …”
Get full text

Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm... by Paolo Iván Cubillo-Leyton, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña

Get full text

Improved performance of single sided axial flux for reduction in cogging torque (IMPACT) by Ahmed Dawood, Junaid Ikram, Muhammad Bilal Riaz, Khurram Saleem Alimgeer, Shumaila Javeed

Get full text

Unleashing Predicting a Comparative Study of Machine Learning for Bankruptcy Risk Prediction by Yupeng Li, Ke Sun

“…Predictive analytics are advanced through the utilization of sophisticated machine learning methodologies, specifically the Random Forest classification model (RFC), The Grasshopper Optimizer Algorithm (GOA), and the Artificial Rabbits Optimizer (ARO). …”
Get full text

Excavating trajectory planning of electric shovel based on dynamic excavating volume prediction by Juan Wu, Rui Liu, Baoguo Lin

Get full text

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
Get full text

Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

Get full text

Deciphering the impact of sepsis phenotypes on improving clinical outcome predictions: a multicenter retrospective analysis based on critical care in China by Luyao Zhou, Weimin Zhang, Min Shao, Cui Wang, Yu Wang

Get full text

Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection by Weichao Liu, Jiapeng Xiao, Rongyuan Liu, Yan Liu, Yunzhu Tao, Tian Zhang, Fuping Gan, Ping Zhou, Yuanbiao Dong, Qiang Zhou

Get full text

Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm by Qianmei Yang, Cuifang Liu, Yongyue Wang, Guifang Dong, Jinghuan Sun

“…We than successfully leveraged machine learning algorithms, particularly the RANDOM FOREST model, to develop a predictive model for sentinel lymph node metastasis in breast cancer. …”
Get full text

INTELLIGENT SYSTEM FOR CLASSIFICATION OF STUDENT PERSONALITY WITH NAIVE BAYES ALGORITHM by Dony Fahrudy, Izza Afkarina, Muhammad Fadli, Rinny Asasunnaja, Wildan Nadiyal Ahsan, Febri Eka Setyawan, Maria Ulfah Siregar

“…The data held are then calculated using the nave Bayes algorithm. Based on the results, there were 12 students correctly predicted and 1 students did not predict correctly so that an accuracy of 92.31% was obtained with an error rate of 7.69%. …”
Get full text

Three-Dimensional Path Planning Optimization for Length Reduction of Optimal Path Applied to Robotic Systems by Ilias Chouridis, Gabriel Mansour, Apostolos Tsagaris

Get full text

Understanding temperature-rain data using ID3 based concept reduction technique in FCA by S. Usharani, S. Kaspar

Get full text

Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development by Biplov Paneru, Durga Prasad Mainali, Bishwash Paneru, Sanjog Chhetri Sapkota

Get full text

Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

Subjects: Get full text

Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
Get full text

Analyzing Financial Stability by Predicting Bankruptcy Situations with Machine Learning by Mohd Naved, Ravi Kumar, Shaiku Saheb

“…Machine learning (ML) may help in bankruptcy prediction by analyzing massive quantities of historical financial data, identifying trends and anomalies that indicate trouble, and developing predictive models to estimate the possibility of default. …”
Get full text

Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…The aim of this research is to compare and analyze the prediction accuracy of machine learning algorithms, i.e., Artificial neural network (ANN), Support vector machine (SVM), Naïve Bayes (NB), Decision tree (DT), Logistic regression (LR), and K-nearest neighbor (KNN) to identify security and performance bugs from the bug repository. …”
Get full text

Energy Consumption Prediction in Iran: A Hybrid Machine Learning and Genetic Algorithm Method with Sustainable Development Considerations by Seyyed Mohammad Mehdi Fatemi Bushehri, Saeed Dehghan Khavari, Seyed Hossein Mirjalili, Hamid Babaei Meybodi, Mohsen Sardari Zarchi

“…The algorithm was able to select 14 features as the most effective indicators in predicting energy consumption from all the 104 ones in the IREC with 500 repetitions. …”
Get full text

Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction by Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos

“…The following objectives were set: i) to compare the efficacy of individual and combined Vis-NIR and pXRF data for the prediction of chemical attributes, using the Random Forest (RF) algorithm, and ii) to compare two methods (Boruta and Principal Component Analysis - PCA) for dimensionality reduction. …”
Get full text