Comparison of Feature Selection and Feature Extraction Role in Dimensionality Reduction of Big Data by Haidar Khalid Malik, Nashaat Jasim Al-Anber, Fuad AbdoEsmail Al- Mekhlafi

“…We applied many classifiers like (Support vector machines, k-nearest neighbors, Decision tree, and Naive Bayes ) to the data of the anthropometric survey of US Army personnel (ANSUR 2) to classify the data and test the relevance of features by predicting a specific feature in USA Army personnel results showing that (k-nearest neighbors) achieved high accuracy (83%) in prediction, then reducing the dimensions by several techniques like (Highly Correlated Filter, Recursive  Feature Elimination, and principal components Analysis) results showing that (Recursive  Feature Elimination) have the best accuracy by (66%), From these results, it is clear that the efficiency of dimension reduction techniques varies according to the nature of the data. …”
Get full text

Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting by C. Jeevakarunya, V. Manikandan

“…In terms of performance, the study assesses the effectiveness of EDW-MKSVR models against those of boosted tree, random forest regression, K-nearest neighbor, support vector regression, and long short term memory. …”
Get full text

The Influence of Data Length on the Performance of Artificial Intelligence Models in Predicting Air Pollution by Mohamed Khalid AlOmar, Faidhalrahman Khaleel, Abdulwahab Abdulrazaaq AlSaadi, Mohammed Majeed Hameed, Mohammed Abdulhakim AlSaadi, Nadhir Al-Ansari

“…In this study, three artificial intelligence (AI) approaches, namely group method of data handling neural network (GMDHNN), extreme learning machine (ELM), and gradient boosting regression (GBR) tree, are used to predict the hourly concentration of PM2.5 over a Dorset station located in Canada. …”
Get full text

Mapping the social-ecological suitability of agroforestry in the US Midwest by Sarah E Castle, Daniel C Miller, Chloe B Wardropper

“…We mapped priority areas where agroforestry is expected to reduce the risk of environmental degradation, provide productive tree growth, and be socially and economically viable. …”
Get full text

Insights on the utilisation of tissue culture to aid new breeding techniques for cowpea (Vigna unguiculata L.) improvement by Malizukiswe Vincent Vacu, Promise Sifiso Nzama, Muyiwa Seyi Adegbaju

Get full text

Topographical Analysis of Spatial Patterns Generated by a Cellular Automaton Model of the Proliferation of a Cancer Cell Line In Vitro by Jacqueline Palmari, Bruno Lafon, Pierre Marie Martin, Christophe Dussert

“…The comparison is made from a topographical point of view through the concept of the minimal spanning tree graph. The agreement between experiment and model is a good starting point to complex models such as cell proliferation under growth effectors or drugs.…”
Get full text

Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…These top-15 feature pairs were fed into five different ML models (decision tree (DT), neural networks (NN), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGB)) for predicting the likelihood of diabetes, while also feeding the direct features (without correlated pairing) separately into the same 5[Formula: see text]ML models. …”
Get full text

Sustainable production through biostimulants under fruit orchards by Vishal Singh Rana, Sunny Sharma, Neerja Rana, Umesh Sharma

Get full text

Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models by Basim Mahbooba, Radhya Sahal, Wael Alosaimi, Martin Serrano

“…The four machine learning techniques are decision tree (DT), K nearest neighbour (KNN), random forest (RF), and naïve Bayes (NB). …”
Get full text

Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning. by M Isabel Ramos, Juan J Cubillas, Ruth M Córdoba, Lidia M Ortega

“…From farmers, to agricultural technicians, researchers and scientists dedicated to the study of the olive tree, to governmental institutions and agricultural associations that provide technical support, advice and regulation to ensure responsible practices and the long-term viability of the olive industry.…”
Get full text

The Importance of Plants in Ancient Cultures Against the Background of New Research Concerning Intelligence of Plants by Agnieszka Tańczuk

“… Juicy fruit, healthy vegetables, herbs for all the ailments, delightful flowers, a shelter under the spreading branches of an old tree - can plants be something more for man, and can they be even equal to him? …”
Get full text

REFINED ESTIMATES OF DIRECT PYROGENIC CARBON EMISSIONS IN RUSSIAN FORESTS BASED ON REMOTE MONITORING DATA FROM 2011 TO 2023 by D. V. Ershov, E. N. Sochilova, K. A. Kovganko

“…The main differences from the estimates in previous our publications are the use of a new version of annually updated products of pre-fire forest combustible fuels (FCF), which include new data on the reserves of FCF in the upper tree canopy, undergrowth, living ground vegetation cover and wood debris. …”
Get full text

Ensemble Classification Model With CFS-IGWO–Based Feature Selection for Cancer Detection Using Microarray Data by Pinakshi Panda, Sukant Kishoro Bisoy, Sandeep Kautish, Reyaz Ahmad, Asma Irshad, Nadeem Sarwar

“…Support vector machines (SVMs), multilayer perceptron (MLP) classification, logistic regression (LR), decision tree (DT), adaptive boosting (AdaBoost) classifier, extreme learning machines (ELMs), and K-nearest neighbor (KNN) are used as classifiers. …”
Get full text

Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG) by Ahmed M. A. Mohamed, Osman N. Uçan, Oğuz Bayat, Adil Deniz Duru

“…Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. …”
Get full text

Resolving Rapid Radiation of Voles and Lemmings (Arvicolinae: Cricetinae, Rodentia) with QuaddRAD Sequencing and Transcriptome Analysis by Natalia Abramson, Elizaveta Skalon, Olga Bondareva, Semen Bodrov, Tatyana Petrova, Ivan Dvoyashov

“…For the first time, whole-genome sequencing data resolved relations within the third radiation wave of the subfamily’s taxa, namely the tribes Arvicolini, Lagurini, and Ellobiusini, which have formed polytomy in mitochondrial trees in earlier articles. This study indicates that divergence dating is highly dependent on the number and position of calibration points in a tree and on taxa sampling. …”
Get full text

Advanced Fraud Detection: Leveraging K-SMOTEENN and Stacking Ensemble to Tackle Data Imbalance and Extract Insights by Nurafni Damanik, Chuan-Ming Liu

“…These results significantly outperform standalone models like XGBoost and Decision Tree, showcasing the strength of the proposed approach. …”
Get full text

Sensitivity Analysis on the Impact of Input Parameters on Seismic Hazard Results: A Case Study of Central America by Carlos Gamboa-Canté, Mario Arroyo-Solórzano, Alicia Rivas-Medina, Belén Benito

“…The accurate estimation of the parameters in recurrence models (declustering and fitting methods), along with the selection of scaling relationships for determining maximum magnitude and the selection of ground motion models (GMMs), enhance control over epistemic uncertainties when constructing the logic tree, minimizing final calculation errors and producing credible results for the study region. …”
Get full text

Mechanical Mastication of Utah Juniper Encroaching Sagebrush Steppe Increases Inorganic Soil N by Kert R. Young, Bruce A. Roundy, Dennis L. Eggett

“…Bare interspaces had 3.0–3.4 times higher inorganic N than interspaces covered with masticated trees during late-summer through winter (P<0.01). …”
Get full text

Microscopical and molecular investigation of Ichthyophthirius multifiliis from fish in Mosul city, Iraq by Esraa A. Altaie, Nadia N. Alhayali

“…Molecular phylogenetic analysis conducted with 18S rRNA gene confirming species identification of one positive isolate out of 13 belonging to the ectoparasite I. multifiliis under the accession number PQ012981 and according to the genetic tree analysis of I. multifiliis showed 100% match with each of the United States isolates for the same species and under the accession numbers KJ690571, KJ690572, KJ690570, KJ690568, KJ690567, KJ690566 and KJ690565 and isolates OM865867 in India and OM302501 in China. …”
Get full text

Parallel Integral Equation-Based Nonoverlapping DDM for Solving Challenging Electromagnetic Scattering Problems of Two Thousand Wavelengths by Qin Su, Yingyu Liu, Xunwang Zhao, Zongjing Gu, Chang Zhai, Zhongchao Lin, Weijun Wu

“…An improved adaptive direction partitioning scheme is applied to the oct-tree of MLFMA to achieve high parallel efficiency. …”
Get full text