What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…This study comprehensively assessed ten widely used data techniques, namely AdaBoost, Bayesian ridge, gradient tree boosting, K-nearest neighbors, Lasso, multivariable linear regression, neural network, random forest, ridge regression, and support vector machine. …”
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What Is Affecting the Residents’ Subjective Perception toward Objective Environment Quality? by Jihong Zhang, Chaopeng Xie, Chuan Chen, Ninghan Xu, Rui Gao

“…In order to analyze the differences between groups, firstly, the important factors driving the differences were extracted by random forest. Secondly, the key individual characteristics were identified by the model based on conditional inference tree. …”
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Parameter Acquisition Study of Mining-Induced Surface Subsidence Probability Integral Method Based on RF-AGA-ENN Model by Jinman Zhang, Liangji Xu, Jiewei Li, Yueguan Yan, Ruirui Xu

“…To obtain more accurate PIM parameters in the absence of observational data, we propose a combined machine learning model (RF-AGA-ENN)—random forest (RF) extracts the best combination of features as the input layer of Elman neural network (ENN); ant colony algorithm (ACO) and genetic algorithm (GA) are combined (called AGA) for the weights and thresholds of ENN optimization. …”
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Design and Evaluation of a Leader–Follower Isomorphic Vascular Interventional Surgical Robot by Pengfei Chen, Yutang Wang, Dapeng Tian

“…The classification process includes time-frequency domain feature extraction, feature selection based on the Relief method and random forest (RF) method, and a BP neural network (NN) classifier. …”
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Detection of multidrug resistant Vibrio parahaemolyticus and anti-Vibrio Streptomyces sp. MUM 178J by Ke-Yan Loo, Loh Teng-Hern Tan, Jodi Woan-Fei Law, Priyia Pusparajah, Learn-Han Lee, Vengadesh Letchumanan

“…This study aimed to investigate the prevalence of MDR V. parahaemolyticus to provide insight into the current antibiotic resistance patterns of this pathogen and to determine potential anti-Vibrio properties of Streptomyces MUM 178J which was previously isolated from the soils of a mangrove forest in Sarawak, Malaysia. Colony morphology and toxR-assay indicated that all samples tested positive for V. parahaemolyticus. …”
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Variability of morphometrical characteristics of needles at a clonal plantation of plus trees of scots pine (Pinus sylvestris L.) by N. N. Besschetnova, V. P. Besschetnov

“…The formation of plus trees assortment for seed orchards is one of the most difficult problems of contemporary forest breeding. This problem is related to the risk of inbreeding depression of the seed progeny of plus trees, which do not have any defense mechanism against self-pollination. …”
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Improved Pedestrian Positioning with Inertial Sensor Based on Adaptive Gradient Descent and Double-Constrained Extended Kalman Filter by Miaoxin Ji, Jinhao Liu, Xiangbo Xu, Yuyang Guo, Zhenchun Lu

“…The Foot-mounted Inertial Pedestrian-Positioning System (FIPPS) based on the Micro-Inertial Measurement Unit (MIMU) is a good choice for the forest fire fighters when the Global Navigation Satellite System is unavailable. …”
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Machine Learning  Modelling of the Relationship between Weather and Paddy Yield in Sri Lanka by Piyal Ekanayake, Windhya Rankothge, Rukmal Weliwatta, Jeevani W. Jayasinghe

“…The significance of the weather indices on the paddy yield was explored by employing Random Forest (RF) and the variable importance of each of them was determined. …”
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An Improved Deep Learning-Based Technique for Driver Detection and Driver Assistance in Electric Vehicles with Better Performance by Gunapriya Balan, Singaravelan Arumugam, Suresh Muthusamy, Hitesh Panchal, Hossam Kotb, Mohit Bajaj, Sherif S. M. Ghoneim, null Kitmo

“…As a part of this research, a driver identification system based on a deep driver classification model (deep neural network as DNN) with feature reduction techniques (random forest as RF and principal component analysis as PCA) is implemented to help automate and aid in crucial jobs such as the brake system in an efficient manner. …”
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Assessing Urban Landscape Variables’ Contributions to Microclimates by Tammy E. Parece, Jie Li, James B. Campbell, David Carroll

“…Using this temperature data, together with six landscape variables, we interpolated (using Kriging and Random Forest) air temperatures across the city for each collection period. …”
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A Multilayer Model Predictive Control Methodology Applied to a Biomass Supply Chain Operational Level by Tatiana M. Pinho, João Paulo Coelho, Germano Veiga, A. Paulo Moreira, José Boaventura-Cunha

“…Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. …”
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Soil Parameter Mapping and Ad Hoc Power Analysis to Increase Blocking Efficiency Prior to Establishing a Long-Term Field Experiment by Doug Collins, Chris Benedict, Andy Bary, Craig Cogger

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An Ecolevel Estimation Method of Individual Driver Performance Based on Driving Simulator Experiment by Yiping Wu, Xiaohua Zhao, Ying Yao, Jian Rong

“…In addition, comparative analysis displayed that the performance of backpropagation neural network based model was better than linear regression based model and random forest based model, from the aspects of elapsed time and prediction accuracy in estimating the ecolevel of driver performance. …”
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A Machine Learning Method to improve Supplier Delivery Appointments in Supply Chain Industries by Anitha Palakshappa, Sumana Maradithaya, Charunayana V

“…Prediction algorithms namely, Logistic Regression (LR), K-Nearest Neighbour (KNN), and Random Forest (RF) are used for forecasting. The appointment is assigned to a supplier based on the delivery date of a previous supplier order. …”
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Dynamic Impacts of Climate and Land-Use Changes on Surface Runoff in the Mountainous Region of the Haihe River Basin, China by Ruonan Li, Hua Zheng, Binbin Huang, Huashan Xu, Yunkai Li

“…Comparing the relative contributions before and after 1998 in the four subbasins, the average influence of climate was found to decline dramatically from 67.1% to 30.5%, while that of land-use increased from 23.9% to 69.5% mainly due to the increase of forest area. Our results revealed that the primary environmental factor responsible for runoff variations was not constant, and an alternation may accentuate the impact and stimulate an abrupt change of runoff in semiarid and semihumid mountainous regions. …”
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An interpretable and stacking ensemble model for predicting heat and mass transfer of desiccant wheel by Mengyang Li, Liu Chen

“…The model uses an integration approach, Light Gradient Boosting Machine, Random Forest and Back Propagation Neural Network models are used as the first-level base models to learn the data, and the Linear Regression model as a meta-model integrates the output of the base model to obtain the final prediction results. …”
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Performance evaluation of brain state discrimination using near-infrared spectroscopy for brain-computer interface: an exploratory case study by Akira Masuo, Takuto Sakuma, Shohei Kato

“…Seventeen trials of the NIRS signal were acquired for each task, and 52 samples with 24-dimensional features per trial data were extracted. Random forest was used as the classifier, and the number of correct responses in the binary discrimination of the brain states were calculated by cross-validation. …”
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Environmental DNA (eDNA) as a tool to detect Arctic grayling and their habitat preferences in the Northwest Territories, Canada by Heather D. Veilleux, Melissa D. Misutka, Morag D. McPherson, Peter A. Cott, Greg G. Goss, Mark Poesch, Chris N. Glover

“…The presence of eDNA was related to habitat metrics via Random Forest and correlation analyses. Riffles and water temperature were identified as being predictive of Arctic grayling eDNA abundance; however, no significant relationship between eDNA abundance and biomass proxies (fish abundance and fork length metrics) could be established. …”
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High-throughput sequence-based microsatellite genotyping for the non-model Neotropical tree species Anadenanthera colubrina (Leguminosae) by Alejandra Lorena Goncalves, María Victoria García, Emilie Chancerel, Olivier Lepais, Myriam Heuertz

“…Background and aims – Anadenanthera colubrina is a Neotropical native forest tree species with significant ecological importance in Seasonally Dry Tropical Forests. …”
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Automated Container Terminal Production Operation and Optimization via an AdaBoost-Based Digital Twin Framework by Yu Li, Daofang Chang, Yinping Gao, Ying Zou, Chunteng Bao

“…Second, we introduce a random forest and XGBoost to compare with AdaBoost to select the best algorithm to train and optimize the DT mechanism model. …”
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