Prediction of canopy mean traits in herbaceous plants by the UAV multispectral data: The quest for a better leaf-to-canopy upscaling method by Yuanqi Shan, Yunlong Yao, Lei Wang, Zhihui Wang, Huaihu Yi, Yi Fu, Weineng Li, Xuguang Zhang, Wenji Wang, Zhongwei Jing

“…This study proposed a novel approach for calculating canopy mean traits using the geometric mean method and compared its performance to that of the CWM methods in combination with three modeling algorithms Partial Least Squares Regression (PLSR), Random Forest regression (RF), and Support Vector Machine regression (SVM). …”
Get full text

Solving the Multi Objective Programming Problem Using Mean and Median Value by Najmaddin Sulaiman, Gulnar Sadiq

“…In this paper, the present algorithm [4] to solve fractional programming problem for multi objective functions, investigate the algorithm to solve linear programming problem for multiobjective functions [2], the computer application of algorithm was tested on a number of numerical examples and modify the approach by using mean and median for values of objective functions, to combine objective function from objective functions for linear programming problem for multi objective functions then it has been improved the above algorithm to solve the problem and computer application of improvement algorithm has been demonstrated by a flow chart and solving numerical examples on the computer then the good results have been often, as compared to the previous method [2].…”
Get full text

K-Means Clustering of Social Studies Performance at Junior High School by Tundo, Syifa Raihanah, Tri Wahyudi, Sugiyono

“…The K-Means Clustering algorithm was chosen because it has proven effective in grouping academic data in various studies. …”
Get full text

Perturbation based privacy preservation and classification using Jaya Algorithm and Dragonfly Inspired Algorithm by Dipanwita Sen, Bhupati Bhusan Mishra, Prasant Kumar Pattnaik

“…Thereafter, the accuracies obtained by a few traditional classification algorithms as well as classifiers based on some meta-heuristic algorithms, are observed . …”
Get full text

Iterative Mean Removal Superimposed Training for SISO and MIMO Channel Estimation by O. Longoria-Gandara, R. Parra-Michel, M. Bazdresch, A. G. Orozco-Lugo

“…The proposed algorithm draws an analogy with the data dependent ST (DDST) algorithm, that is, extracts the cycling mean of the data, but in this case at the receiver's end. …”
Get full text

A Novel Mathematical Model for Radio Mean Square Labeling Problem by Elsayed Badr, Shokry Nada, Mohammed M. Ali Al-Shamiri, Atef Abdel-Hay, Ashraf ELrokh

“…We also show that the computational results and their analysis prove that the proposed approximate algorithm overcomes the integer linear programming model (ILPM) according to the radio mean square number. …”
Get full text

Multi-objective synthesis planning by means of Monte Carlo Tree search by Helen Lai, Christos Kannas, Alan Kai Hassen, Emma Granqvist, Annie M. Westerlund, Djork-Arné Clevert, Mike Preuss, Samuel Genheden

Get full text

Penerapan Algoritma K-Means Clustering Untuk Mengetahui Kemampuan Karyawan IT by Dina Zakiyah, Nita Merlina, Nissa Almira Mayangky

“…Therefore, we need a technique that can group the employee's ability to determine the employee's ability using the K-Means Clustering Algorithm method. The data grouping is done in several stages, namely, inputting data into Ms. …”
Get full text

Perbandingan Aplikasi Algoritma Kernel K-Means pada Graf Bipartit dan K-Means pada Matriks Dokumen- Istilah dalam Dataset Penelitian Covid-19 RISTEKBRIN by Budi Nugroho

“…As comparison, we applied original k-means algorithm on the document-term matrix of the dataset. …”
Get full text

Machine state classification of electric track circuit by means of logistic regression by D. V. Borisenko, I. V. Prisukhina, S. A. Lunev

Get full text

Application of Artificial Intelligence using K-Means for Programming Question Assessment by Waliyyudin Waliyyudin, Ichsan Ibrahim

“…The method employed is the K-Means clustering algorithm, chosen for its ability to group answers based on similarities in logic and code structure rather than mere textual similarity. …”
Get full text

Polyspectral mean based time series clustering of Indian stock market by Dhrubajyoti Ghosh

“…Abstract In this study, we employ k-means clustering algorithm of polyspectral means to analyze 49 stocks in the Indian stock market. …”
Get full text

MEANS OF DRUG DELIVERY IN THE EVENT OF INHALATION THERAPY IN CHILDREN: SELECTION CRITERIA by L. R. Selimzyanova, E. A. Vishneva, E. A. Promyslova

“…The article presents an algorithm of selecting means of inhalation drug delivery for use in children and the review of currently marketed inhalers, their advantages and drawbacks.…”
Get full text

Ellipsoidal <i>K</i>-Means: An Automatic Clustering Approach for Non-Uniform Data Distributions by Alaa E. Abdel-Hakim, Abdel-Monem M. Ibrahim, Kheir Eddine Bouazza, Wael Deabes, Abdel-Rahman Hedar

“…Traditional <i>K</i>-means clustering assumes, to some extent, a uniform distribution of data around predefined centroids, which limits its effectiveness for many realistic datasets. …”
Get full text

Comparison of Dynamic Programming Algorithm and Greedy Algorithm on Integer Knapsack Problem in Freight Transportation by Global Ilham Sampurno, Endang Sugiharti, Alamsyah Alamsyah

“…Knapsack is a place used as a means of storing or inserting an object. The purpose of this research is to know how to get optimal solution result in solving Integer Knapsack problem on freight transportation by using Dynamic Programming Algorithm and Greedy Algorithm at PT Post Indonesia Semarang. …”
Get full text

Wind Turbine Placement Optimization by means of the Monte Carlo Simulation Method by S. Brusca, R. Lanzafame, M. Messina

“…This paper defines a new procedure for optimising wind farm turbine placement by means of Monte Carlo simulation method. To verify the algorithm’s accuracy, an experimental wind farm was tested in a wind tunnel. …”
Get full text

Penerapan Algoritme Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance (LMKHNCN) Untuk Klasifikasi Hasil Kinerja Pegawai Negeri Sipil by Adam Syarif Hidayatullah, Fitra Abdurrachman Bachtiar, Imam Cholissodin

“…This study is use classification technique Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance (LMKHNCN). This method is modified base algorithm of K-Nearest Neighbor (KNN). …”
Get full text

ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition. by David Koslicki, Saikat Chatterjee, Damon Shahrivar, Alan W Walker, Suzanna C Francis, Louise J Fraser, Mikko Vehkaperä, Yueheng Lan, Jukka Corander

“…The aggregation of reads is a pre-processing approach where we use a standard K-means clustering algorithm that partitions a large set of reads into subsets with reasonable computational cost to provide several vectors of first order statistics instead of only single statistical summarization in terms of k-mer frequencies. …”
Get full text

ESTIMATION OF HELICOPTER BLADE POSITION BY MEANS OF TWO-CHANNEL MEASURING SYSTEM by V. A. Anikin, N. V. Kim, P. D. Prokhorov

“…The main difficulty is that blade is a highly dynamic moving object.This work suggests two-channel measuring system of helicopter blades position. …”
Get full text

Leveraging prior mean models for faster Bayesian optimization of particle accelerators by Tobias Boltz, Jose L. Martinez, Connie Xu, Kathryn R. L. Baker, Zihan Zhu, Jenny Morgan, Ryan Roussel, Daniel Ratner, Brahim Mustapha, Auralee L. Edelen

“…In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. …”
Get full text