Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…By employing the Dijkstra algorithm, route optimization resulted in a significant reduction in average route length, from 12.94 ± 3.5 km to 9.42 ± 2.67 km, representing a 9-42% improvement. …”
Get full text

Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal... by Abhijeet Das

“…Basically, all approaches cumulatively predicted surface WQI with lower accuracy. Overall, the LOR, KNN, ANN, and SVM algorithms were all surpassed by the RF algorithm. …”
Get full text

Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia by Yi Wei Chen, Shan He, Yu Wang, Lian Ying Hu, Qin Kai Chen, Si Yi Liu

“…Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. …”
Get full text

Azo Dyes and the Microbial World: Synthesis, Breakdown, and Bioactivity by Valery M. Dembitsky, Alexander O. Terent’ev

“…Using mathematical algorithms and the PASS program, researchers predict new potential applications based on their structure–activity relationships. …”
Get full text

Strategies to Reduce Left Anterior Descending Artery and Left Ventricle Organ Doses in Radiotherapy Planning for Left-Sided Breast Cancer by Umut Diremsizoglu, Nezihan Topal, Aykut Oguz Konuk, Ibrahim Halil Suyusal, Dogacan Genc, Onur Ari, Hasan Furkan Cevik, Aysegul Ucuncu Kefeli, Maksut Gorkem Aksu, Emine Binnaz Sarper

“…Conclusions: We achieved significant reductions in all heart, LAD, and LV parameters without making any changes to the planned treatment volume coverage by adding LAD and LV OARs to the optimization algorithms. …”
Get full text

Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…Experimental results of antennas modeling demonstrate that the proposed algorithm improves the prediction accuracy and fitting performance relative to BNN. …”
Get full text

Crystal structure generation with autoregressive large language modeling by Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo

“…Seeding structure prediction algorithms with quality generated candidates can overcome a major bottleneck. …”
Get full text

Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

“…When combined with mixture cure models, they can effectively improve the performance of mixture cure models, distinguish between susceptible and non-susceptible individuals, and accurately predict the influencing factors and their magnitude of incidence and latency.…”
Get full text

Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

“…Regression analysis of such a system has predicted that the performance gap will persist with varying network nodes and increasing time limits. …”
Get full text

A comparison of several intrusion detection methods using the NSL-KDD dataset by hazem salim abdullah

“…This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. …”
Get full text

Optimising Daily Fantasy Sports Teams with Artificial Intelligence by Beal Ryan, Norman Timothy J., Ramchurn Sarvapali D.

“…To this end, we propose a number of new models and algorithms to solve the team formation problems posed by DFS. …”
Get full text

Estimation of CO₂ Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach by Seval Ene Yalçın

“…The proposed approach incorporates artificial neural networks, machine learning, and deep learning algorithms. The case of Turkey was considered as an example. …”
Get full text

Leveraging AI for Enhanced Operational Risk Management in Sports Events by Jibraili Malak, Rharib Abderrahim, Jibraili Zineb

“…The results reveal that, although AI offers many opportunities to minimise operational failures, concerns remain about the complexity of algorithms and the management of real-time data. Despite these obstacles, the paper concludes that future prospects are promising, with potential innovations such as the automation of critical processes and the prediction of operational incidents.…”
Get full text

Novel meta-ensemble modelling approach and comparison of machine-learning models for rebar price estimation by Sahin Tolga Guvel, Abdulkadir Budak, Ibrahim Karataş

“…The voting meta-ensemble machine-learning algorithm exhibited the best performance for all lag periods investigated. …”
Get full text

Conceptualizing an AI-based Police Robot for Preventing Online Child Sexual Exploitation and Abuse: by Nina Sunde, Inger Marie Sunde

“…Given the advancements in machine learning algorithms, PrevBOT may provide predictions concerning age and gender behind online aliases engaged in sexualized speech with children and assist the police in identifying former CSEA offenders who resume the criminal activity online. …”
Get full text

Energy Consumption Optimization for an Electric Delivery Vehicle by Andrzej Łebkowski

“…This publication proposes an electronic Energy Consumption Optimizer (ECO) that predictively uses information about the shape of the route and speed limits on its individual sections to control the motor speed and gear changes in the gearbox. …”
Get full text

Psychological Stress Identification and Evaluation Method Based on Mobile Human-Computer Interaction Equipment by Na Zhang

“…Through the BP of mobile human-computer interaction equipment, hereditary, genetic algorithms, and Hi-PLS regression method in the artificial neural network, the psychological pressure of college students is identified, evaluated, and predicted from three dimensions such as learning, life, and personal events. …”
Get full text

Confidence-Guided Frame Skipping to Enhance Object Tracking Speed by Yun Gu Lee

“…The proposed method determines the need for intervention by the robust algorithm based on the predicted confidence level. …”
Get full text

Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry by Bowen Cai

“…Therefore, this article uses deep learning algorithms to forecast and analyze the new energy industry, starting from the financial information released by new energy vehicle companies in their annual reports, in order to make basic judgments and help policy makers and enterprises in the new energy vehicle industry.…”
Get full text

Utility of positron emission tomography–computed tomography in the evaluation of fever of unknown origin in a resource-limited tropical nation by Sohini Das, Sowmya Sathyendra, Julie Hephzibah, Reka Karuppusami, Karthik Gunasekaran, Nylla Shanthly, Angel Miraclin, Ramya Iyadurai

“…We also looked at laboratory parameters as predictors of contributory PET-CT scans and propose an algorithm for evaluation of FUO in resource-limited tropical regions. …”
Get full text