Results 61 to 70 of about 676,778 (198)

Estimation of Percentage on Malnutrition Occurrences in East Java Using Geographically Weighted Regression Model [PDF]

, 2015
The Province of East Java has its own characteristics that differentiate it from any other regions. Dissimilarities in characteristics of a region may encompass issues such as social, economic, cultural, parenting, education, and the environment, so as ...
Djuraidah, A. (Anik), Hardinsyah, H. (Hardinsyah), Hutabarat, I. M. (Ida), Saefuddin, A. (Asep)   +3 more
core  

Distributed network-based integrated navigation methodfor surface ship formation

Zhongguo Jianchuan Yanjiu
Objective In systematic operations, ship formation navigation faces such challenges as equipment damage, electromagnetic interference and complex operational environments.
Wentao HUANG, Zhao ZHONG, Wenhua ZHAI, Yuan ZHANG, Chuanhua KANG   +4 more
doaj   +1 more source

Time Difference of Arrival (TDoA) Localization Combining Weighted Least Squares and Firefly Algorithm

Sensors, 2019
Time difference of arrival (TDoA) based on a group of sensor nodes with known locations has been widely used to locate targets. Two-step weighted least squares (TSWLS), constrained weighted least squares (CWLS), and Newton−Raphson (NR) iteration ...
Peng Wu, Shaojing Su, Zhen Zuo, Xiaojun Guo, Bei Sun, Xudong Wen   +5 more
doaj   +1 more source

A weighted least squares method for scattered data fitting

Journal of Computational and Applied Mathematics, 2008
The authors present a weighted least squares method in order to find a smooth surface which approximately produces a given set of scattered data points in \(\mathbb{R}^3\). The data are assumed to be contaminated by noise. When the data are reliable, the corresponding weight is 1: when the data are not reliable, the weight (smaller than 1, e.g.
Zhou, Tianhe, Han, Danfu
openaire   +2 more sources

Algorithms for Spectral Analysis of Irregularly Sampled Time Series [PDF]

In this paper, we present a spectral analysis method based upon least square approximation. Our method deals with nonuniform sampling. It provides meaningful phase information that varies in a predictable way as the samples are shifted in time.
Adolf Mathias, Detlef Seese, Florian Grond, Hans H. Diebner, Miguel Canela, Ramon Guardans   +5 more
core   +1 more source

Novel Node Localization Algorithm Based on Nonlinear Weighting Least Square for Wireless Sensor Networks

International Journal of Distributed Sensor Networks, 2012
Positioning of the location information of wireless sensor network nodes is one of the key issues in wireless sensor network applications. The traditional node positioning method based on least-square algorithm heavily depends on the ranging accuracy ...
Fu Xiao, Mingtan Wu, Haiping Huang, Ruchuan Wang, Sudan Wang   +4 more
doaj   +1 more source

A Data Fusion Orientation Algorithm Based on the Weighted Histogram Statistics for Vector Hydrophone Vertical Array

Sensors, 2020
In this paper, we propose a data fusion algorithm based on the weighted histogram statistics (DF-WHS) to improve the performance of direction-of-arrival (DOA) estimation for the vector hydrophone vertical array (VHVA).
Yan Liang, Zhou Meng, Yu Chen, Yichi Zhang, Mingyang Wang, Xin Zhou   +5 more
doaj   +1 more source

Efficiency and adverse impact of general classification decisions [PDF]

, 2010
Classification decisions relate to situations in which a battery of predictors is used to assign individuals to a number of different trajectories. De Corte (2000) proposed a method to estimate the classification efficiency in case the assignment of ...
De Corte, Wilfried, Druart, Celina
core   +1 more source

Comparisons of Methods of Estimation for a New Pareto-type Distribution

Statistica, 2019
Bourguignon et al. (2016) introduced a new Pareto-type distribution to model income and reliability data. The aim of this paper is to estimate the parameters of this distribution from both frequentist and Bayesian view points.
Ali Saadati Nik, Akbar Asgharzadeh, Saralees Nadarajah   +2 more
doaj   +1 more source

Physics-guided Deep Learning for Power System State Estimation

Journal of Modern Power Systems and Clean Energy, 2020
In the past decade, dramatic progress has been made in the field of machine learning. This paper explores the possibility of applying deep learning in power system state estimation.
Lei Wang, Qun Zhou, Shuangshuang Jin
doaj   +1 more source