Auxiliary Particle Flow Track-Before-Detect Algorithm for Marine Neighboring Weak Targets by Fan Zhang, Chang Liu

“…Simulation experiments indicate that compared with track-before-detect algorithms based on parallel partition (PP) and auxiliary parallel partition (APP), the proposed algorithm shows an increase of 43.1% and 25.8% in detection probability at 6 dB, and a reduction of 76.6% and 66.2% in Root Mean Square Error (RMSE). …”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…This study introduces an AI-driven predictive fire alarm and evacuation model that leverages machine learning algorithms and real-time environmental sensor data to anticipate fire hazards before ignition, improving emergency response efficiency. …”
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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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Binary Classification of Customer’s Online Purchasing Behavior Using Machine Learning by Ahmad Aldelemy, Raed A. Abd-Alhameed

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A Novel Approach for Enhancing Plant Leaf Classification With the Binary Cuckoo Search Algorithm by Mohammad Subhi Al-Batah, Mohammad Ryiad Al-Eiadeh, Yazan Alnsour

“…In this study, we introduced a model for classifying a variety set of plant leaves using different techniques such as factorization machine (FM), dimensionality reduction (DR), and ensemble learning (EL). In our study, FM is used as a classification algorithm, whereas DR is included in two stages, namely, feature extraction (FE) and feature selection (FS). …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…The systemic solution to prevent rework in sustainable buildings is to predict the occurrence of rework. This research pursues two key objectives: first, to prioritise the primary predictors of rework in sustainable buildings; second, to evaluate the most suitable machine learning algorithms for accurately modelling rework occurrences by classifying the extent of rework in the sustainable buildings. …”
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Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

“…The hybrid prediction model has a smaller relative error value compared to a single algorithm, with a maximum value of less than 0.2. …”
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Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC) by Mohammad Hassan Hashemi, Ulas Kilic

“…Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. …”
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Short-Term Power Load Forecasting Method based on Glowworm Swarm Optimization Algorithm by Haihong FAN

“…With the rapid development of the power industry, the power load prediction is becoming more and more important in recent years, and short-term load prediction plays an extremely important role in dispatching and market operation of the power system. …”
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Revolution in flow cytometry: using artificial intelligence for data processing and interpretation by Szymon Bierzanowski, Szymon Bierzanowski, Krzysztof Pietruczuk

“…Similarly, multivariate analysis and dimension reduction are also commonly attempted. The integration of advanced AI algorithms with FC methods contributes to a better understanding and interpretation of biological data, opening up new opportunities in research and clinical diagnostics. …”
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Prediction of Traffic Accident Severity Based on Random Forest by Jianjun Yang, Siyuan Han, Yimeng Chen

“…Random forest was used to rank the importance of 12 accident features, and 7 important accident features were finally adopted. By comparing the algorithms and optimizing the results, the prediction model of traffic accident degree with higher accuracy is finally obtained.…”
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Electrical Grounding Fault Prediction of EMU Traction Motor by Xuemiao PANG, Chunxing PEI, Chunguang YAN, Dongxing WANG, Jie JIANG

“…It shows that the prediction accuracy of the three algorithms is higher than 84% at all. …”
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Smart Vehicle Parking System with Rfid-Based Authentication and Ai-Powered Slot Detection by Kalaivani S, Parnasree Chakraborty, Mahalakshmi alias Isakki

Subjects: “…environmental impact reduction…”
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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities by Shoaib Hassan, Qianmu Li, Khursheed Aurangzeb, Affan Yasin, Javed Ali Khan, Muhammad Shahid Anwar

“…The results show that researchers used these algorithms in eight major RE activities. Those activities are requirements analysis, failure prediction, effort estimation, quality, traceability, business rules identification, content classification, and detection of problems in requirements written in natural language. …”
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Predicting Hit Songs Using Audio and Visual Features by Cheng-Yuan Lee, Yi-Ning Tu

“…However, we combined audio and visual data to make predictions on 1000 YouTube songs. In total, 1000 songs were grouped into two categories based on YouTube view counts: popular and non-popular. …”
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Prediction of Chemical Gas Emissions Based on Ecological Environment by Guobin Chen, Shijin Li

“…Relevant intelligent chemical algorithms control the emission of chemical gases, which can effectively reduce emissions and predict emissions more accurately. …”
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Statistical Prediction of Summer Rainfall and Vegetation in the Ethiopian Highlands by Mark R. Jury

“…After step-wise multivariate regression, the leading predictors are: surface temperature across Europe (cold-favourable), 850 mb zonal winds over the tropical Atlantic (easterly-favourable), and surface temperature in the tropical Indian Ocean (cold-favourable). Predictive algorithms for early and late rainfall exhibit a consistent r2 fit of ~0.50, while those for vegetation reach ~0.65 in late summer, indicating that fluctuations in food resources could be forewarned.…”
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Electromechanical Battery EMB Mass Minimization taking into Account its Electrical Machines Rotor Energy by Podgornovs Andrejs, Sipovichs Antons

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Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

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Prediction Models for Diabetes in Children and Adolescents: A Review by Livija Cveticanin, Marko Arsenovic

“…Newly identified factors for differentiating between types of diabetes are discussed, alongside an overview of various machine learning and deep learning algorithms specifically adapted for diabetes prediction in children and adolescents. …”
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