Data Science Application for Creation of Maternal Morbidity and Mortality Predictive Software by Rúsbel Domínguez-Domínguez, Germán H. Alférez, Verenice González-Mejia, Norbet Donías

Get full text

Predictive Beamforming With Active Inference Under Continuous Time-Varying Channels by Naoki Nishio, Tatsuya Otoshi, Masayuki Murata

“…To address this issue, we propose a method that combines hierarchical codebooks with active inference to predict the optimal beam rather than search for it. …”
Get full text

Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…By incorporating a service-level score algorithm based on the TextBlob NLP library, each post is accurately classified and utilized as a feature in a supervised machine-learning classification system. …”
Get full text

Design and Practical Evaluation of Robust Model Predictive Wind Turbine Control by Andreas Klein, Thorben Wintermeyer‐Kallen, János Zierath, Kevin Kluge, Dirk Abel, Heike Vallery, Maximilian Basler

“…We evaluate the proposed control algorithm in terms of time‐domain performance and power curve in simulation. …”
Get full text

A machine learning-based predictive model for predicting early neurological deterioration in lenticulostriate atheromatous disease-related infarction by Zhuangzhuang Jiang, Dongjuan Xu, Hongfei Li, Xiaolan Wu, Yuan Fang, Chen Lou

“…Background and aimThis study aimed to develop a predictive model for early neurological deterioration (END) in branch atheromatous disease (BAD) affecting the lenticulostriate artery (LSA) territory using machine learning. …”
Get full text

The Electricity Load Prediction Model for Residential Buildings: A Critical Review of Output Types, Prediction Methods and Driving Factors by Zhenjing Wu, Min Qi, Weiling Zhang, Xudong Zhang, Qiang Yang, Wenyuan Zhao, Bin Yang, Zhihan Lyu, Faming Wang, Zhichao Wang

“…Predictive model building methods were classified as classical, algorithms based on Machine Learning (ML) or Deep Learning (DL) and hybrid methods. …”
Get full text

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study. by Michael King, Louise Marston, Igor Švab, Heidi-Ingrid Maaroos, Mirjam I Geerlings, Miguel Xavier, Vicente Benjamin, Francisco Torres-Gonzalez, Juan Angel Bellon-Saameno, Danica Rotar, Anu Aluoja, Sandra Saldivia, Bernardo Correa, Irwin Nazareth

“…<h4>Conclusions</h4>The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.…”
Get full text

Adaptive Sensor Activation Algorithm for Target Tracking in Wireless Sensor Networks by Wei Zhou, Weiren Shi, Xiaogang Wang, Kai Wang

“…In this paper, we propose an energy-efficient sensor activation protocol based on predicted region technique, called predicted region sensor activation algorithm (PRSA). …”
Get full text

Interpretable Reinforcement Learning for Sequential Strategy Prediction in Language-Based Games by Jun Zhao, Jintian Ji, Robail Yasrab, Shuxin Wang, Liang Yu, Lingzhen Zhao

“…However, existing models often struggle with poor adaptability and limited interpretability when applied to dynamic language prediction tasks such as <b>Wordle</b>. To address these challenges, this study proposes an interpretable reinforcement learning framework based on an Enhanced Deep Deterministic Policy Gradient (Enhanced-DDPG) algorithm. …”
Get full text

Fair and Transparent Student Admission Prediction Using Machine Learning Models by George Raftopoulos, Gregory Davrazos, Sotiris Kotsiantis

“…Student admission prediction is a crucial aspect of academic planning, offering insights into enrollment trends, resource allocation, and institutional growth. …”
Get full text

Quantitatively Detecting Camellia Oil Products Adulterated by Rice Bran Oil and Corn Oil Using Raman Spectroscopy: A Comparative Study Between Models Utilizing Machine Learning Alg... by Henan Liu, Sijia Ma, Ni Liang, Xin Wang

“…In addition to performance fluctuations with varying regression algorithms, the output for feature extraction method also played a vital role in ultimate prediction performance.…”
Get full text

An Optimized Power Load Forecasting Algorithm Based on VMD‐SMA‐LSTM by Wei Liu, Fan Hua, Yongping Cui, Yangchao Xu, Han Liu

“…Case studies demonstrate that the proposed algorithm outperforms other power load forecasting methods in prediction accuracy.…”
Get full text

Research and application of adaptive algorithm for 5G voice quality evaluation by Yuxiang ZHAO, Yaxin JI, Li YU, Tianyi ZHOU, Hang ZHOU

“…MOS (mean opinion score) is usually used to evaluate voice quality in the industry.It can objectively and fairly reflect the user’s voice service perception.It is difficult and costly to obtain data by road test, so a trained supervised learning model is usually used to predict the MOS score.However, the operator voice data has the characteristics of low percentage of MOS low score data and time sequence change, which affects the accuracy and generalization of the model prediction.Based on the study of existing data acquisition systems and machine learning algorithms of operators, an adaptive algorithm for MOS evaluation of 5G speech quality was proposed.Firstly, POLQA algorithm test equipment based on full parameter evaluation obtained training data to ensure the accuracy of training samples.Secondly, by means of data enhancement, the difficulty of acquiring poor quality samples was solved.Finally, based on the adaptive algorithm selection, the optimal MOS prediction model could be selected periodically and dynamically according to the timing changes of data features, so as to achieve large-scale and intelligent evaluation of 5G voice quality.…”
Get full text

An Extended Firefly Algorithm for Enhanced Information Diffusion with Multi-Factor Considerations by Amjad Alloush, Ghaida Rebdawi:, Mohammad Saeed Abou Trab

“…Understanding and predicting how information spreads in online social networks is a crucial yet complex task, especially with the growing influence of content type, user engagement, and social dynamics. …”
Get full text

A Data-Driven Front Tracking Algorithm for Autonomous Undersea Vehicles by Jieyang LU, Yongpeng WEN, Qian GUO, Xinke ZHU, Junsheng JIAO

“…To meet the requirement for adaptive observation of autonomous undersea vehicles(AUVs), a data-driven ocean front tracking algorithm was designed. This algorithm constructed a hybrid temperature field prediction model based on Gaussian process regression(GPR) and particle swarm optimization(PSO). …”
Get full text

The GENDULF algorithm: mining transcriptomics to uncover modifier genes for monogenic diseases by Noam Auslander, Daniel M Ramos, Ivette Zelaya, Hiren Karathia, Thomas O. Crawford, Alejandro A Schäffer, Charlotte J Sumner, Eytan Ruppin

Get full text

Inversion algorithm of black carbon mixing state based on machine learning by Z. Tian, Z. Tian, J. Wang, J. Wang, J. Wang, J. Wang, C. Liu, C. Liu, J. Xing, J. Wang, J. Wang, Z. Zhang, Z. Zhang, Y. Jin, Y. Jin, S. Shen, S. Shen, B. Wang, B. Wang, W. Nie, W. Nie, X. Huang, X. Huang, A. Ding, A. Ding

Get full text

Kinematics Analysis of Grasping Manipulator based on ART-RBF Learning Algorithm by Kai Wang, XiaoJin Wan

“…The results show that the soft competition algorithm can improve the prediction accuracy to a certain extent. …”
Get full text

Direct methanol fuel cells parameter identification with enhanced algorithmic technique by Manish Kumar Singla, Muhammed Ali S.A, Ramesh Kumar, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…A number of optimization techniques have been adopted: Particle Swarm Optimization (PSO), Dragonfly Algorithm (DA), Harris Hawk Optimizer (HHO), Rhinoceros Search Algorithm (RSA), Artificial Hummingbird Algorithm (AHA), and its enhanced version, Enhanced artificial hummingbird algorithm (EAHA). …”
Get full text

From energy to cellular forces in the Cellular Potts Model: An algorithmic approach. by Elisabeth G Rens, Leah Edelstein-Keshet

“…We predict the traction forces exerted by single cells of various shapes and sizes on a 2D substrate. …”
Get full text