DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding by Maryam Mirsadeghi, Majid Shalchian, Saeed Reza Kheradpisheh

“…Backpropagation is the foremost prevalent and common algorithm for training conventional neural networks with deep construction. …”
Get full text

Physical education and sport activity assessment tool-based machine learning predictive analysis for planification of training sessions by Mohamed Rebbouj, Said Lotfi

“…Background and purpose The aim of this study is to incorporte machine learning techniques in physical education activities assessment so we can plan a training session and learning cycle based on predictive analyses using machine learning algorithms. …”
Get full text

Investigating the effects of previous injury on subsequent training loads, physical fitness, and injuries in youth female basketball players by Yuanqi Huang, Shaonan Wang, Changfei Li, Yukun Wang, Zhanshuang Bai, Zhanshuang Bai, Binghao Lv, Yuheng Gui, Zhongjian Wei

“…However, few studies have evaluated whether previous injury influences them. …”
Get full text

Advanced comparative analysis of machine learning algorithms for early Parkinson's disease detection using vocal biomarkers by Ajay Kumar, Jay Parkash Singh, Priyanka Paygude, Rachan Daimary, Sandeep Prasad

Get full text

Study for Predicting Land Surface Temperature (LST) Using Landsat Data: A Comparison of Four Algorithms by Elhadi K. Mustafa, Yungang Co, Guoxiang Liu, Mosbeh R. Kaloop, Ashraf A. Beshr, Fawzi Zarzoura, Mohammed Sadek

Get full text

Algorithm for Constructing the Hazard Function of the Extended Cox Model and its Application to the Prostate Cancer Patient Database by I. I. Mikulik, G. M. Zharinov, A. Yu. Kneev

“…It simulates the reproduction of flowering plants using pollinating insects and consists of three parts: an ant colony algorithm, a genetic algorithm, and an ant pollinator algorithm. …”
Get full text

Machine learning for asphaltene polarizability: Evaluating molecular descriptors by Arun K. Sharma, Owen McMillan, Selsela Arsala, Supreet Gandhok, Rylend Young

“…A dataset of 255 asphaltene structures was analyzed using stratified sampling, generating 10 independent training (80 %) and testing (20 %) splits. The Wolfram Language’s Predict function evaluated multiple machine learning algorithms—including Random Forest, Decision Tree, Gradient Boosted Trees, Nearest Neighbors, Linear Regression, Gaussian Process, and Neural Network—through an automated model selection process, serving as an AutoML framework. …”
Get full text

The use of deep learning algorithm and digital media art in all-media intelligent electronic music system. by Yingming Zheng

“…Even in the case of task error, the algorithm still shows good training results. H-DDPG algorithm has good effect for complex task processing. …”
Get full text

A novel time difference of arrival localization algorithm using a neural network ensemble model by Zhenkai Zhang, Feng Jiang, Boyuan Li, Bing Zhang

“…The estimation accuracy of the locating system is evaluated through experimental measurements. The simulation results show that the proposed algorithm is efficient in improving the generalization ability and localization precision of the neural network ensemble model.…”
Get full text

Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…The findings show that boosting algorithms, particularly LightGBM, are highly effective for path loss prediction in LoRaWANs.…”
Get full text

Red Fox Optimization-Based Estimation Algorithms for Splitting Tensile Strength of Basalt Fiber Reinforced Concrete by Xiao Wu, Daoyong Zhu, Qin Yan

Get full text

Convolution neural network algorithm-based fouling organisms classification model of seawater circulation cooling system by ZHANG Yi

“…The cross entropy loss function and accuracy rate were used as model evaluation indicators to train the model. The model could be used for automatic identification of fouling organisms in automatic dosing equipment. …”
Get full text

Survivor detection approach for post earthquake search and rescue missions based on deep learning inspired algorithms by Rajendrasinh Jadeja, Tapankumar Trivedi, Jaymit Surve

“…This paper presents a novel approach to survivor detection using a snake robot equipped with deep learning (DL) based object identification algorithms. We evaluated the performance of three main algorithms: Faster R-CNN, Single Shot MultiBox Detector (SSD), and You Only Look Once (YOLO). …”
Get full text

Accuracy of cephalometric landmark and cephalometric analysis from lateral facial photograph by using CNN-based algorithm by Yui Shimamura, Chie Tachiki, Kaisei Takahashi, Satoru Matsunaga, Takashi Takaki, Masafumi Hagiwara, Yasushi Nishii

“…This study evaluates the estimation accuracy by the algorithm trained on a dataset of 2320 patients with added malocclusion patients and the analysis values. …”
Get full text

Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics by Yujian Hui, Hengda Hu, Jinghua Xiang, Xingye Du

“…Abstract Objective This study aimed to evaluate the performance of five machine learning algorithms in predicting tibial intramedullary nail length using patient demographic data (gender, height, age, and weight), with the goal of developing a clinically relevant and accurate predictive model. …”
Get full text

An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection. by Mohd Sakib, Tamanna Siddiqui, Suhel Mustajab, Reemiah Muneer Alotaibi, Nouf Mohammad Alshareef, Mohammad Zunnun Khan

“…This study proposes an ensemble approach that integrates a genetic algorithm with multiple forecasting models to optimize feature selection. …”
Get full text

Enhancing flood susceptibility mapping in Meghna River basin by introducing ensemble Naive Bayes with stacking algorithms by Abu Reza Md. Towfiqul Islam, Md. Uzzal Mia, Nourin Akter Nova, Rabin Chakrabortty, Md. Sanjid Islam Khan, Bonosri Ghose, Subodh Chandra Pal, A. B. M. Mainul Bari, Edris Alam, Md Kamrul Islam, Mohammed Ali Alshehri, Hazem Ghassan Abdo, Romulus Costache

“…This article intends to assess flood susceptibility mapping in Meghna River basin (MRB) and identified flood susceptible regions using three benchmark models including random forest (RF), support vector machine (SVM) and bagging with Naïve Bayes (NB) stacking ensemble algorithms (e.g. RF-NB; SVM-NB and Bagging-NB). The flood sample was partitioned into a training set (70%), and a validation set (30%), and the capability of prediction of flood-influencing variables was quantified by the multi-collinearity test. …”
Get full text

Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms by Mengdi Liang, Yuelin Liu, Yue Huang, Ge Ma, Xu Han, Shuaikang Li, Jing Hang, Hui Xie, Lin Chen, Xiaoan Liu, Shui Wang, Tiansong Xia

“…Radiomic analysis included 124 tumors from 69 patients, randomly split into a 3:1 ratio for training (96 cases) and validation (28 cases). Three machine learning algorithms were applied for feature selection. …”
Get full text

Predicting Financial Distress through Ranking Working Capital Management Components Using Random Forest Algorithm by Pouya Sadeghi, Daryush Farid, Hamid Reza Mirzaei, Abolfazl Dehghani

“…Subsequently, the predictive power of 7 key working capital management components in forecasting financial distress was tested using Python software and the random forest algorithm.The random forest method is based on ensemble learning, wherein the data are split into training and testing sets. …”
Get full text

Construction and validation of a prognostic model for NK/T-cell lymphoma based on random survival forest algorithm by HUANG Zhen, HUANG Zhen, WU Yazhou

“…The patients were divided into a training cohort (n=471) and a validation cohort (n=203) in a 7∶3 ratio. …”
Get full text