Transfer and deep learning models for daily reference evapotranspiration estimation and forecasting in Spain from local to national scale by Yu Ye, Aurora González-Vidal, Miguel A. Zamora-Izquierdo, Antonio F. Skarmeta

“…This study compares standard ML and Deep Learning (DL) algorithms for estimating and forecasting daily ET0 at different spatial scales in Spain. …”
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Prediction of shut-off head for centrifugal pumps based on grey theory and GA-BP neural network by Dehui Yu, Jinfeng Zhang, Shouqi Yuan, Wensheng Ma, Xiaobang Bai, Yan Chen, Chao Wang

“…This paper presents a predictive model based on extensive experimental data, employing a back propagation (BP) neural network optimized via grey theory and genetic algorithms (GAs). Data were collected from 141 single-stage volute centrifugal pumps, and grey theory was used to analyze nine critical parameters of the impeller and volute, yielding five optimal input schemes with correlation coefficients exceeding 0.6. …”
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Model order reduction of boiler system using nature-inspired metaheuristic optimization of PID controller by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…This study proposes a dual-stage optimization framework that integrates balanced truncation-based model order reduction with nature-inspired metaheuristic algorithms for PID controller tuning to address these issues. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…In order to improve the operation efficiency of the urban rail transit system and achieve the goal of smart operations, this paper applies machine learning algorithms and completes the feature engineering of urban rail transit passenger flow data in terms of time, space and external factors. …”
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Contextual information based anomaly detection for multi-scene aerial videos by Girisha S, Ujjwal Verma, Manohara M M. Pai, Radhika M. Pai

“…Further, the lack of standard UAV-based anomaly detection datasets has restricted the development of novel algorithms. In this regard, the present work proposes a novel multi-scene aerial video anomaly detection dataset with frame-level annotations. …”
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Unravelling the importance of spatial and temporal resolutions in modeling urban air pollution using a machine learning approach by Alireza Zhalehdoost, Mohammad Taleai

“…Among the evaluated algorithms, MLP consistently achieves the highest predictive accuracy across both temporal and spatial scenarios. …”
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Risk assessment of the top 50 drugs associated with drug-induced orthostatic hypotension: a disproportionality analysis of the FAERS and JADER databases by Gaocan Ren, Xiansu Chi, Pingping Huang, Jinhui Zhang, Yanqiu Ding, Lijun Guo, Qinghua Shang, Xiaochang Ma

“…Adverse event reports of orthostatic hypotension from Q1 2004 to Q3 2024 were obtained from the FAERS and JADER databases. We employed algorithms such as the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) for signal detection. …”
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Teaching design students machine learning to enhance motivation for learning computational thinking skills by Hung-Hsiang Wang, Chun-Han Ariel Wang

“…Students using Weka spent more time focusing on model training and tended to improve their algorithmic thinking, and the introduction of Weka appeared to enhance their motivation to learn. …”
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Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism by Adel Binbusayyis, Mohemmed Sha

“…To enhance prediction accuracy, a proposed smart city system utilizes the Household Energy Consumption dataset, employing deep learning algorithms. In the beginning, data pre-processing addresses missing values and performs feature scaling for normalizing independent variables. …”
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On Introduction to q1,q2-Linear Diophantine Fuzzy Sets and Their Applications by Muhammad Bilal Khan, Adrian Marius Deaconu, Javad Tayyebi, Bandar Bin-Mohsin, Loredana Ciurdariu, Miguel Vivas Cortez, Nurnadiah Zamri

“…In the latter half of the paper, different ranking algorithms based on proposed aggregation operators are presented to address a realistic assessment of the patient’s high blood pressure conditions is conducted to demonstrate the viability and value of the suggested strategies.…”
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Topic Words-Based Multilingual Hateful Linguistic Resources Construction for Developing Multilingual Hateful Content Detection Model Using Deep Learning Technique by Naol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra Abate

“…Among applied deep learning algorithms with Ethiopian language linguistic resources, word2vec-based multilingual lexicons with convolutional neural network (CNN) outperform than others. …”
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Discovering Travel Community for POI Recommendation on Location-Based Social Networks by Lei Tang, Dandan Cai, Zongtao Duan, Junchi Ma, Meng Han, Hanbo Wang

“…The proposed POI recommendation algorithms can be deployed in certain online transportation systems and can serve over 100,000 users.…”
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Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation by Li Hu, Xilingyuan Chen, Rentao Yu

“…This study was designed to develop and compare different models for predicting patients with cellulitis developing sepsis during hospitalisation.Design This is a retrospective cohort study.Setting This study included both the development and the external-validation phases from two independent large cohorts internationally.Participants and methods A total of 6695 patients with cellulitis in the Medical Information Mart for Intensive care (MIMIC)-IV database were used to develop models with different machine-learning algorithms. The best models were selected and then externally validated in 2506 patients with cellulitis from the YiduCloud database of our university. …”
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Solar radiation prediction: A multi-model machine learning and deep learning approach by C Vanlalchhuanawmi, Subhasish Deb, Md. Minarul Islam, Taha Selim Ustun

“…Focusing on five input variables—solar irradiance, dew point, temperature, relative humidity, and wind speed—this study evaluates the predictive performance of 13 data-driven models, comprising ten machine learning (ML) and three deep learning (DL) algorithms. Among them, gradient boosting regressor (GBR) and recurrent neural network (RNN) emerged as top performers in ML and deep learning, respectively. …”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…It examines the integration of advanced sensors, remote sensing, and machine learning algorithms in precision agriculture, assessing their roles in optimizing irrigation and nutrient management. …”
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A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…Abstract Optimization algorithms play a fundamental role in training neural networks. …”
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Efficient and Composable Masked AES S-Box Designs Using Optimized Inverters by Vedad Hadžic, Roderick Bloem

“… Hardware implementations of cryptographic algorithms are susceptible to power analysis attacks, allowing attackers to break the otherwise strong security guarantees. …”
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MODELING THE BEHAVIOR OF ENTERTAINMENT CONTENT CONSUMERS TAKING INTO ACCOUNT DIGITAL TECHNOLOGIES by Olga Zyma

“…The article develops a flowchart of the decision-making process regarding content consumption, covering motivation, algorithmic or manual search, evaluation of content characteristics, alignment with expectations, and the final decision – whether to watch or reject the content. …”
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The profile of patients with haemophilia managed at a haemophilia treatment centre in Pretoria, Gauteng by Lethukuthula Mafisa, Abegail N. Dlova, Vanessa Moodley

“…Study outputs have included compilation of diagnostic and management algorithms to optimise haemophilia care at DGMAH.…”
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P-68 LIVGUARD, A DEEP NEURAL NETWORK FOR CIRRHOSIS DETECTION IN LIVER ULTRASOUND (USD) IMAGES by DIEGO ARUFE, Pablo Gomez del Campo, Ezequiel Demirdjian, Carlos Galmarini

“…Further work is required to validate this algorithmic framework in prospective cohorts of patients in additional clinical trials and/or real-world datasets.…”
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