Dynamic Optimization of Bus Line Schedule in Commuter Corridor Based on Bus IC Card Data by Zhihong Li, Han Xu, Shiyao Qiu, Jun Liu, Kairan Yang, Jiahao Wu

“…To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. …”
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Intelligent Trust Evaluation Method for Underwater Sensor Networks Based on Fuzzy Clustering and Dynamic Weight Allocation by Zhaohui WANG, Guangjie HAN, Jiaxin DU, Chuan LIN, Lei WANG

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YOLOv7-DWS: tea bud recognition and detection network in multi-density environment via improved YOLOv7 by Xiaoming Wang, Xiaoming Wang, Zhenlong Wu, Guannan Xiao, Guannan Xiao, Chongyang Han, Cheng Fang

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Developing an Integrative Data Intelligence Model for Construction Cost Estimation by Zainab Hasan Ali, Abbas M. Burhan, Murizah Kassim, Zainab Al-Khafaji

“…In this research, extreme gradient boosting is developed as an advanced input selector algorithm and coupled with three AI models, including random forest (RF), artificial neural network (ANN), and support vector machine (SVM) for cost estimation. …”
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A Non-Invasive Fetal QRS Complex Detection Method Based on a Multi-Feature Fusion Neural Network by Zhuya Huang, Junsheng Yu, Ying Shan, Xiangqing Wang

“…Finally, the deep neural network using three multi-feature fusion strategies—feature-level fusion, decision-level fusion, and model-level fusion—achieves the effect of quickly identifying fetal QRS complexes. …”
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A Cooperative Generation Expansion Planning of Microgrids to Improve the Resiliency of Active Distribution Networks by Mohammad Hossein Atazadegan, Esmaeel Rokrok, Meysam Doostizadeh

“…In this case, the multi objective optimization problem, including the objective functions of total cost and environmental pollution, has been solved using fuzzy decision-making and multi-objective improved golden ratio optimization algorithm based on the Pareto front.…”
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A Framework for Automatic IT Architecture Modeling: Applying Truth Discovery by Margus Välja, Robert Lagerström, Ulrik Franke, Göran Ericsson

“…The usefulness of the proposed framework is demonstrated in a study where models using three tools are created, namely; Archi, securiCAD, and EMFTA.…”
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Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…The experimental results show that the proposed method is competitive compared to three state-of-the-art algorithms.…”
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Synthetic data in medicine: Legal and ethical considerations for patient profiling by Maja Nisevic, Dusko Milojevic, Daniela Spajic

“…Synthetic data is increasingly used in healthcare to facilitate privacy-preserving research, algorithm training, and patient profiling. By mimicking the statistical properties of real data without exposing identifiable information, synthetic data promises to resolve tensions between innovation and data protection. …”
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Fast SVM-based Multiclass Classification in Large Training Sets by M. Yu. Kurbakov, V. V. Sulimova

“…Experimental investigation of proposed methods was made on three large handwritten digit images data sets of different size and one large intrusion detection data set. …”
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Improving myocardial infarction diagnosis with Siamese network-based ECG analysis. by Vaibhav Gadag, Simrat Singh, Anshul Harish Khatri, Shruti Mishra, Sandeep Kumar Satapathy, Sung-Bae Cho, Abishi Chowdhury, Amrit Pal, Sachi Nandan Mohanty

“…It was converted into three classes Myocardial Infarction, Abnormal heartbeat, and Normal.…”
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Heuristic Approach to Comparing the Environmental Impacts of Carbon Nanotube Production Methods by Ahmad Atif Fikri, Irham Fadlika, Albarrobi Nabila Saeful, Krisna Dwipa Muhdi, Daniel Febrian Pratama, Nasir Garba Bello

“…One way to overcome this problem is by using the heuristic method for forecasting environmental impact, which can be done with the Multi-Criteria Decision Analysis algorithm. The method can calculate uncertainty in each scenario, by normalizing the given load value. …”
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Contagious disease outbreaks: Distinguishing between constant and variable order using the SEIAR model by S.Sepehr Tabatabaei, Mohammadreza Dehghan

“…The methodology involves a three-phase process: selecting an appropriate model, estimating its parameters, and identifying the order of derivation. …”
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UAV-Enabled Inspection System With No-Fly Zones: DRL-Based Joint Mobile Nest Scheduling and UAV Trajectory Design by Jin Dai, Yunfei Gao, Chao Cai, Wei Xiong, Manjia Liu

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Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks by Salmah Fattah, Ismail Ahmedy, Mohd Yamani Idna Idris, Abdullah Gani

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Research on Automatic Test Case Generation Technology Based on Finite State Machines and Function Block Diagrams by LI Ning, XIONG Yan, DING Yaoguo

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FEATURE SELECTION IN THE TASK OF MEDICAL DIAGNOSTICS ON MICROARRAY DATA by N. G. Zagoruiko, O. A. Kutnenko, I. A. Borisova, V. V. Dyubanov, D. A. Levanov, O. A. Zyranov

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Ensemble network using oblique coronal MRI for Alzheimer’s disease diagnosis by Cunhao Li, Zhongjian Gao, Xiaomei Chen, Xuqiang Zheng, Xiaoman Zhang, Chih-Yang Lin

“…In this study, based on the ADNI dataset and previous clinical diagnostic experience, we propose a method using oblique coronal MRI to assist in diagnosis. We developed an algorithm to extract oblique coronal slices from 3D MRI data and used these slices to train classification networks. …”
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Online prediction of optimal deep brain stimulation contacts from local field potentials in Parkinson’s disease by Marjolein Muller, Stefano Scafa, Ibrahem Hanafi, Camille Varescon, Chiara Palmisano, Saskia van der Gaag, Rodi Zutt, Niels A. van der Gaag, Carel F. E. Hoffmann, Jocelyne Bloch, Mayte Castro Jiménez, Julien F. Bally, Philipp Capetian, Ioannis U. Isaias, Eduardo M. Moraud, M. Fiorella Contarino

“…Using beta-band power measures (13–35 Hz), we ranked channels based on clinical contact-level choices and developed two prediction algorithms: (i) a “decision tree” method for in-clinic use and (ii) a “pattern based” method for offline validation. …”
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A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles by Shuai Sun, Jun Zhang, Jun Bi, Yongxing Wang

“…The study is innovative in its application of machine learning method, the gradient boosting decision tree algorithm, on the driving range prediction which includes a very large number of factors that cannot be considered by conventional regression methods. …”
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