scholarly journals Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation

2018 ◽  
Vol 8 (10) ◽  
pp. 1862 ◽  
Author(s):  
Shuopeng Wang ◽  
Peng Yang ◽  
Hao Sun
Keyword(s):  
Cluster Analysis ◽  
Interpolation Method ◽  
Reference Points ◽  
Matching Method ◽  
Two Stage ◽  
Positioning Accuracy ◽  
Acoustic Localization ◽  
Database Construction ◽  
Iterative Interpolation ◽  
Stage Matching

Fingerprinting acoustic localization usually requires tremendous time and effort for database construction in sampling phase and reference points (RPs) matching in positioning phase. To improve the efficiency of this acoustic localization process, an iterative interpolation method is proposed to reduce the initial RPs needed for the required positioning accuracy by generating virtual RPs in positioning phase. Meanwhile, a two-stage matching method based on cluster analysis is proposed for computation reduction of RPs matching. Results reported show that, on the premise of ensuring positioning accuracy, two-stage matching method based on feature clustering partition can reduce the average RPs matching amount to 30.14% of the global linear matching method taken. Meanwhile, the iterative interpolation method can guarantee the positioning accuracy with only 27.77% initial RPs of the traditional method needed.

Two-stage Matching and Pricing with Applications to Ride Hailing

2020 ◽  
Author(s):  
Yiding Feng ◽  
Rad Niazadeh ◽  
Amin Saberi
Keyword(s):  
Two Stage ◽  
Stage Matching

Characterization of Glycosphingolipids and Their Diverse Lipid Forms through Two-Stage Matching of LC-MS/MS Spectra

2021 ◽  
Vol 93 (6) ◽  
pp. 3154-3162
Author(s):  
Laura S. Bailey ◽  
Fanran Huang ◽  
Tianqi Gao ◽  
Jinying Zhao ◽  
Kari B. Basso ◽  
...  
Keyword(s):  
Two Stage ◽  
Stage Matching

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals A Compound Wind Power Forecasting Strategy Based on Clustering, Two-Stage Decomposition, Parameter Optimization, and Optimal Combination of Multiple Machine Learning Approaches

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3586 ◽  
Author(s):  
Sizhou Sun ◽  
Jingqi Fu ◽  
Ang Li
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Search Algorithm ◽  
Interpolation Method ◽  
Least Square ◽  
Support Vector ◽  
Two Stage ◽  
Wind Power Forecasting ◽  
Power Forecasting

Given the large-scale exploitation and utilization of wind power, the problems caused by the high stochastic and random characteristics of wind speed make researchers develop more reliable and precise wind power forecasting (WPF) models. To obtain better predicting accuracy, this study proposes a novel compound WPF strategy by optimal integration of four base forecasting engines. In the forecasting process, density-based spatial clustering of applications with noise (DBSCAN) is firstly employed to identify meaningful information and discard the abnormal wind power data. To eliminate the adverse influence of the missing data on the forecasting accuracy, Lagrange interpolation method is developed to get the corrected values of the missing points. Then, the two-stage decomposition (TSD) method including ensemble empirical mode decomposition (EEMD) and wavelet transform (WT) is utilized to preprocess the wind power data. In the decomposition process, the empirical wind power data are disassembled into different intrinsic mode functions (IMFs) and one residual (Res) by EEMD, and the highest frequent time series IMF1 is further broken into different components by WT. After determination of the input matrix by a partial autocorrelation function (PACF) and normalization into [0, 1], these decomposed components are used as the input variables of all the base forecasting engines, including least square support vector machine (LSSVM), wavelet neural networks (WNN), extreme learning machine (ELM) and autoregressive integrated moving average (ARIMA), to make the multistep WPF. To avoid local optima and improve the forecasting performance, the parameters in LSSVM, ELM, and WNN are tuned by backtracking search algorithm (BSA). On this basis, BSA algorithm is also employed to optimize the weighted coefficients of the individual forecasting results that produced by the four base forecasting engines to generate an ensemble of the forecasts. In the end, case studies for a certain wind farm in China are carried out to assess the proposed forecasting strategy.

scholarly journals A two-stage biomass model to assess the English Channel cuttlefish (Sepia officinalis L.) stock

2014 ◽  
Vol 71 (9) ◽  
pp. 2457-2468 ◽  
Author(s):  
Michaël Gras ◽  
Beatriz A. Roel ◽  
Franck Coppin ◽  
Eric Foucher ◽  
Jean-Paul Robin
Keyword(s):  
Reference Points ◽  
Sea Surface ◽  
Sepia Officinalis ◽  
Sustainable Utilization ◽  
English Channel ◽  
Two Stage ◽  
Stock Biomass ◽  
Exploitation Rate ◽  
Spawning Stock ◽  
Age Structured

Abstract The English Channel cuttlefish (Sepia officinalis) is the most abundant cephalopod resource in the Northeast Atlantic and one of the three most valuable resources for English Channel fishers. Depletion methods and age-structured models have been used to assess the stock, though they have shown limitations related to the model assumptions and data demand. A two-stage biomass model is, therefore, proposed here using, as input data, four abundance indices derived from survey and commercial trawl data collected by Ifremer and Cefas. The model suggests great interannual variability in abundance during the 17 years of the period considered and a decreasing trend in recent years. Model results suggest that recruitment strength is independent of spawning–stock biomass, but appears to be influenced by environmental conditions such as sea surface temperature at the start of the life cycle. Trends in exploitation rate do not reveal evidence of overexploitation. Reference points are proposed and suggestions for management of the sustainable utilization of cuttlefish in the English Channel are advanced.

scholarly journals The geolect of Plungė in terms of regressive assimilation of vowels I, U

2020 ◽  
pp. 1-19
Author(s):  
Simona Vyniautaitė
Keyword(s):  
Cluster Analysis ◽  
Quantitative Analysis ◽  
Reference Points ◽  
Research Model ◽  
Limb Reduction ◽  
Audio Recordings ◽  
Main Variable ◽  
Variable Feature ◽  
Dual Core ◽  
Main Distinguishing Feature

Based on dialectometric methods, the article discusses the geolect of Plungė in terms of regressive assimilation of vowels i, u. The study material consists of about 9 hours of audio recordings, 57 sentences, recited by nine presenters of younger, middle and older generations. 6 words were chosen in which regressive assimilation of vowels can take place, i. e., the words with vowels i, u in accented, unaccented and shifted accent positions. Quantitative analysis of the material (sentences read by the presenters) was performed with the tools of the computer program Gabmap. Pseudo maps of networks, reference points, cluster analysis, as well as differential dialectal features were analyzed. The analysis performed using dialectometry methods shows that differences in limb reduction, word stem, consonant softening become apparent, but in many cases regressive assimilation of vowels i, u becomes the main variable feature. The operation/inaction of the regressive assimilation of vowels i, u is greatly influenced by accent. When vowels are accented, presenters of all generations pronounce them without regressive vowel assimilation. When the vowel i is unaccented, it is assimilated, and the vowel u is spelled narrowly by only a third of the presenters. Dual behavior exists in cases where vowels receive a shifted accent. The pronunciation of both vowels is approximate. Maintaining the main distinguishing feature of the residents of Plungė from the dialect of the residents of Telšiai, although inconsistent, would allow predicting that the linguistic dialect peculiarity of this area could compete with the language code of Telšiai – based on the Samogitian regiolect – or whether the regiolect itself would be / become dual-core (more detailed research based on a multi-faceted research model is needed to confirm this statement). The effect of regressive assimilation in the Plungė dialect, in the geolectic zone in general, can be both a proof of resemblance to the northern Samogitian Telšiai residents and a sign of a decrease in the importance of assimilation as a distinctive feature of the dialects.

scholarly journals Robust palmprint identification using efficient enhancement and two-stage matching technique

2020 ◽  
Vol 14 (11) ◽  
pp. 2333-2342
Author(s):  
Mubeen Ghafoor ◽  
Syed Ali Tariq ◽  
Imtiaz A. Taj ◽  
Noman M. Jafri ◽  
Tehseen Zia
Keyword(s):  
Two Stage ◽  
Palmprint Identification ◽  
Matching Technique ◽  
Stage Matching

scholarly journals Improvement and Assessment of the Absolute Positioning Accuracy of Chinese High-Resolution SAR Satellites

2019 ◽  
Vol 11 (12) ◽  
pp. 1465
Author(s):  
Deng ◽  
Zhang ◽  
Cai ◽  
Xu ◽  
Zhao ◽  
...  
Keyword(s):  
High Resolution ◽  
Propagation Delay ◽  
Reference Points ◽  
Calibration Model ◽  
Land Resource ◽  
Positioning Accuracy ◽  
Geometric Calibration ◽  
Atmospheric Propagation ◽  
Absolute Positioning ◽  
The Absolute

In recent years, China has launched YaoGan-13 and GaoFen-3, high-resolution synthetic aperture radar (SAR) satellites that can acquire global high-resolution images. The absolute positioning accuracy of such satellites is important for mapping areas without ground reference points and for automated processing. However, satellites without geometric calibration have poor absolute positioning accuracy, greatly restricting their application (e.g., land resource surveys). Therefore, they cannot meet national demands for high-resolution SAR images with good geometric accuracy. Here, we propose a series of methods to improve the absolute positioning accuracy of YaoGan-13 and GaoFen-3, such as the multiple-image combined calibration strategy and geometric calibration model for a real continuously moving configuration, including consideration of atmospheric propagation delay. Using high-accuracy ground control data collected from different areas, the 2-D and 3-D absolute positioning accuracies of YaoGan-13 and GaoFen-3 were assessed after implementation of the improvement measures. Experimental results showed that, after calibration, the 2-D absolute positioning accuracy of YaoGan-13 and GaoFen-3 are improved from 43.86 m to 2.57 m and from 30.34 m to 4.29 m, respectively. In addition, the 3-D absolute positioning accuracies of YaoGan-13 in plane and elevation are 3.21 m and 2.22 m, respectively. Improving the absolute positioning accuracy of these satellites could broaden the scope of their potential applications in the future.

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