Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms? by Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper

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Human fall direction recognition in the indoor and outdoor environment using multi self-attention RBnet deep architectures and tree seed optimization by Awais Khan, Jung-Yeon Kim, Chomyong Kim, Muhammad Attique Khan, Hyojin Shin, Jiyoung Woo, Yunyoung Nam

“…To optimize feature selection and improve classification performance while reducing computational costs, we employed the tree seed algorithm on the self-attention features of 7-RBNet and 9-RBNet self-attention models. …”
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Design strategy of advanced generation breeding population of Pinus tabuliformis based on genetic variation and inbreeding level by Chengcheng Zhou, Fan Sun, Zhiyuan Jiao, Yousry A. El-Kassaby, Wei Li

“…Based on genetic distance estimates using molecular markers, our comparative seed orchard design analysis showed that the Improved Adaptive Genetic Programming Algorithm (IAPGA) reduced the average inbreeding coefficient by 14.36% and 14.73% compared to sequential and random designs, respectively. …”
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Does the implementation of Automatic Individual Tree Crown Delineation (ITCD) impact the early detection of bark beetle (BB) infestation in Norway spruce forests? by S. Bijou, L. Kupková, L. Červená, J. Lysák

“…Treetop detection was performed using local maxima filtering, while four ITCD algorithms: Buffer, Marker-Controlled Watershed Segmentation, thiessen polygons, and seeded region growing, were used for crown delineation. …”
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Evaluation and prediction of the physical properties and quality of Jatobá-do-Cerrado seeds processed and stored in different conditions using machine learning models by Daniel Fernando Figueiredo Spengler, Paulo Carteri Coradi, Dágila Melo Rodrigues, Izabela Cristina de Oliveira, Dalmo Paim de Oliveira, Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro

“…Data were analyzed on Weka software (Waikato Environment for Knowledge Analysis) version 3.9.5. testing the following models: Pearson correlation, Artificial Neural Networks, decision tree algorithms RepTree and M5P, Random Forest, and Linear Regression. …”
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RAD-Seq-derived SSR markers: a new paradigm for genetic analysis and construction of genetically improved production populations in Pinus koraiensis by Pingyu Yan, Wanying Zhang, Junfei Hao, Xiaotian Miao, Jun Wu, Zixiong Xie, Zhixin Li, Lei Zhang, Hanguo Zhang

“…Significant differences in cone production were observed between the plus trees (P<0.01). A production population of 20 individuals was constructed via the simulated annealing algorithm, which exhibited a more reasonable mating system (F=−0.028) and demonstrated superior cone production compared with that of the plus tree population, with an increase of 79.6%. …”
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FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

“…This study proposes a hybrid FOX-TSA algorithm to optimize the MLP model. The hybrid algorithm synergises the Fox Optimization Algorithm's exploration capabilities with the Tree-Seed Algorithm's exploitation strengths. …”
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Machine Learning Ensemble Classifiers for Feature Selection in Rice Cultivars by Chandrakumar Thangavel, D Sakthipriya

“…Selecting a rice cultivar requires considering local environmental and seed factors. This research examines classification algorithms like K-Nearest Neighbor (KNN), Decision Tree (DT), NaiveBayes (NB), Support Vector Machine (SVM), and Random Forest (RF) with wrapper feature selection techniques like SFFS, SBEFS, CBFS, VIF, and RANDIM for environmental and seed data. …”
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An IPv6 target generation approach based on address space forest by Shunlong Hao, Liancheng Zhang, Hongtao Zhang, Lanxin Cheng, Yi Guo, Zhanbo Li, Bin Lin, Haojie Zhu, Mingyue Ren, Lanyun Zhang

“…Due to the uneven distribution of IPv6 seed addresses and irreversibility of clustering in existing IPv6 target generation algorithms, the number of low-dimensional patterns in single-tree algorithms like 6Scan and 6Tree, or dual-tree algorithms like HMap6, is limited. …”
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Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

“…The findings were contrasted to those from various algorithms, such as whale optimization algorithm, multi-verse optimizer, sine cosine algorithm, arithmetic optimization algorithm, particle swarm optimization, red kite optimization algorithm, tree-seed algorithm, and white shark optimizer. …”
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Hilbert-Curve Based Data Aggregation Scheme to Enforce Data Privacy and Data Integrity for Wireless Sensor Networks by Yong-Ki Kim, Hyunjo Lee, Min Yoon, Jae-Woo Chang

“…To preserve data privacy, we make use of both a seed exchange algorithm and Hilbert-curve based data encryption. …”
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Non-Destructive Detection of Current Internal Disorders and Prediction of Future Appearance in Mango Fruit Using Portable Vis-NIR Spectroscopy by Jasciane da Silva Alves, Bruna Parente de Carvalho Pires, Luana Ferreira dos Santos, Tiffany da Silva Ribeiro, Kerry Brian Walsh, Ederson Akio Kido, Sergio Tonetto de Freitas

“…Five models were evaluated: two tree-based algorithms (J48 and random forest), one neural network (multilayer perceptron, MLP), and two SVM training algorithms (sequential minimal optimization, SMO, and LibSVM). …”
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Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Layth Hamad, Mohammad Alkhedher

“…Using advanced machine learning, PIORS can distinguish between various oil types such as sesame, black seed, flaxseed, and almond oils, ensuring the quality and safety of the final product. …”
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Context-Aware Deep Learning Model for Yield Prediction in Potato Using Time-Series UAS Multispectral Data by Suraj A. Yadav, Xin Zhang, Nuwan K. Wijewardane, Max Feldman, Ruijun Qin, Yanbo Huang, Sathishkumar Samiappan, Wyatt Young, Francisco G. Tapia

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Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The six classical machine algorithms including Classified Regression Tree (CART), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), Stepwise Regression (STR) and Gradient Boosting Machine (GBM) were used for training. …”
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Predicting adolescent psychopathology from early life factors: A machine learning tutorial by Faizaan Siddique, Brian K. Lee

“…The best performing algorithms were elastic net and gradient boosted trees. …”
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