Comparative Analysis of Machine Learning Algorithms and Statistical Techniques for Data Analysis in Crop Growth Monitoring with NDVI by M. Arunachalam, S. Sekar, A. M. Erdmann, V. V. Sajith Variyar, R. Sivanpillai

“…Results generated from ML algorithms were compared to the output generated by the ISODATA algorithm. …”
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Oil well productivity capacity prediction based on support vector machine optimized by improved whale algorithm by Kuiqian Ma, Chunxin Wu, Yige Huang, Pengfei Mu, Peng Shi

“…Residual sum of squares (R2) values for SVM optimized by grid search optimization, whale algorithm and improved whale algorithm are 0.372, 0.939 and 0.941 respectively. …”
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355 Validation of an artificial intelligence Algorithm for predicting diagnosis-related groups in a community health system by Angela Muhanga, King Jason, Xsolis Mueller, Jennifer L. Sanger, Julie M. Bartlett, Brian N. Manz, James W. Spiten, Matthew J. Overgaard, Shauna M. Wang Hanyin

“…This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. …”
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Accuracy of Smartphone-Mediated Snore Detection in a Simulated Real-World Setting: Algorithm Development and Validation by Jeffrey Brown, Zachary Mitchell, Yu Albert Jiang, Ryan Archdeacon

“…The Bland-Altman analysis indicated a mean bias of −29.8 (SD 41.7) snores per hour, and the Spearman correlation analysis revealed a strong positive correlation (rsP ConclusionsThe SleepWatch snore detection algorithm demonstrates high accuracy and compares favorably with other snore detection apps. …”
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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…Experiments conducted on the public remote sensing image dataset FAIR1M demonstrated that the YOLOv8n algorithm achieved a mean average precision (mAP) of 81.8% for aircraft category recognition tasks. …”
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Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms by Mengdi Liang, Yuelin Liu, Yue Huang, Ge Ma, Xu Han, Shuaikang Li, Jing Hang, Hui Xie, Lin Chen, Xiaoan Liu, Shui Wang, Tiansong Xia

“…Three machine learning algorithms were applied for feature selection. Then, all the selected features were used for the construction of the prediction model via four machine learning algorithms. …”
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Evaluating the generalizability of an automated coronary artery calcium segmentation and scoring algorithm using multi-vendor dataset by Doyoung Park, Jedidiah Ng, Yixin Zhong, Chun Sheng Alvin Tan, Xiaomeng Wang, Gillianne Geet Yi Lai, Liang Zhong, Su Kai Gideon Ooi, Daniel Shao Weng Tan, Lohendran Baskaran

“…And Bland-Altman plot analysis was conducted to examine the agreement between the CAC score derived from the prediction results and the ground truth. The proposed algorithm exhibited a mean absolute difference of less than 5% between the per-lesion Dice scores of the validation and test sets, indicating good generalizability on test sets comprised of data from unseen scanners during the training and validation phases. …”
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An urban land surface temperature and emissivity separation algorithm from ASTER TIR data and its application by Jinglun Li, Kun Li, Yonggang Qian, Xianhui Dou, Qijin Han, Jian Zeng, Hang Zhao, Qiongqiong Lan, Zhaopeng Xu, Jiayi Bai, Baoan Wei, Xining Liu, Feng Wang, Juntao Yang, Yueming Wang

“…Simulation results show that the root mean squared errors (RMSEs) of the urban canopy BTs are about 0.2 K and 1.2 K using the XGBoost algorithm and split window (SW) algorithm, respectively. …”
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Design of the optimal groundwater quality monitoring network using a genetic algorithm based optimization approach by Somaye Janatrostami, Ali Salahi

“…Materials and methods: Genetic optimization algorithm (GA) was used to search for optimal quality monitoring network. …”
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Hyperspectral Estimation of Chlorophyll Content in Ginseng Fruit Leaves Based on Wavelet Transform and VCPA-GA Algorithm by Guo Jinfeng, Zhang Zhicong, Umut Hasan, Zhou Zhongye, Xu Wenyu, Yusup Ahmat

“…This is because the wavelet transform process has some errors that increase with the number of decomposition layers. (2) The VCPA-GA hybrid variable selection algorithm merges the strengths of the VCPA and GA, addressing the tendency of the VCPA to select fewer variables and overcoming GA's limitations in handling many variables which can lead to overfitting, providing a theoretical basis for estimating ginseng fruit LCC using hyperspectral remote sensing. (3) Among the four machine-learning models, predictions from to 1-2 and 6-7 layers were generally lower than those of the 0 layer, while predictions from the 3–5 layers are higher, showing an overall trend of initial increase followed by a decrease as the number of wavelet decomposition layers increased. (4) Ginseng fruit leaf hyperspectral data processed by the DWT-VCPA-GA algorithm with a 4-layer DWT spectrum yielded the best predictive performance in the BP-AdaBoost regression model, with R2=0.919, mean absolute percentage error = 2.090%, and relative percentage difference = 3.900. (5) After optimizing the BPNN regression model with various algorithms, only some optimized models improved their predictive performance and accuracy to a certain extent, making the choice of the right optimization algorithm crucial for model improvement.…”
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Intelligent recognition algorithm and application of coal mine overhead passenger device based on multiscale feature fusion by Beijing XIE, Heng LI, Hang DONG, Zheng LUAN, Ben ZHANG, Xiaoxu LI

“…The recall is 93.3%, representing an improvement of 9.8%, and the mean average precision is 95.6%, indicating a 7.7% increase. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…[Methods]The YOLOv11-AP2S model enhanced the YOLOv11 algorithm by incorporating a series of improvements to its backbone network, neck, and head components. …”
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Prediction of drop size distribution and mean drop size in an L-shaped pulsed packed column using artificial neural network (ANN) model and semi-empirical correlation by Ali Ravandeh, Sajad Khooshechin

“…The ANN model was trained using the Levenberg–Marquardt algorithm and demonstrated excellent predictive performance, achieving R2 values of 0.981 and 0.986 for drop size distribution and mean drop size, respectively. …”
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Iraqi Stock Market Prediction Using Artificial Neural Network and Long Short-Term Memory by Sama Hayder Abdulhussein AlHakeem, Nashaat Jasim Al-Anber, Hayfaa Abdulzahra Atee, Mahmod Muhamad Amrir

“…In this paper, two models were proposed to predict the Iraqi stock markets index through the use of artificial neural networks (ANN) and a long short-term memory (LSTM) algorithm where Iraqi stock market data were used from 2017 to 2021 and good results were achieved in the prediction where the long short-term memory (LSTM) algorithm reached a mean square error (MSE) rate of as little as 0.0016 while the artificial neural network (ANN) algorithm reached error rate 0.0055. …”
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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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Automated Image-Based Wound Area Assessment in Outpatient Clinics Using Computer-Aided Methods: A Development and Validation Study by Kuan-Chen Li, Ying-Han Lee, Yu-Hsien Lin

“…K-means clustering is a machine learning algorithm that segments the wound region by grouping pixels in an image according to their color similarity. …”
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PERFORMANCE DEGRADATION ASSESSMENT OF ROLLING BEARING BASED ON SINGLE RING THEOREM IN RANDOM MATRIX THEORY by SHAN Qiang, NI GuangXian, WANG Heng

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A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm by Chunhua Ju, Chonghuan Xu

“…In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. …”
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Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms by Liang Huang, Xueqin Yu, Xiaoqing Zuo

“…To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. …”
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Classical Data in Quantum Machine Learning Algorithms: Amplitude Encoding and the Relation Between Entropy and Linguistic Ambiguity by Jurek Eisinger, Ward Gauderis, Lin de Huybrecht, Geraint A. Wiggins

“…The <i>Categorical Compositional Distributional</i> (DisCoCat) model has been proven to be very successful in modelling sentence meaning as the interaction of word meanings. Words are modelled as quantum states, interacting guided by grammar. …”
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