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1

Adams, Catherine M., i David W. Biers. "Effect of Pairted Comparison Weighting and Weighting Context". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, nr 37 (lipiec 2000): 610–13. http://dx.doi.org/10.1177/154193120004403717.

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The present study compared three subjective workload measurement techniques—a unidimensional scale (UW) and two mutidimenional scales (TLX and ModSWAT)–using a continuous memory task. ModSWAT is a technique that uses the sum of the SWAT dimensions to form the workload composite rather than the standard conjoint measurement procedure. Both weighted and unweighted workload measures were obtained for the two multidimensional scales. The paired-comparison technique used by TLX was employed to weight the three SWAT dimensions. For both multidimensional scales, weighting context was also varied. Paired comparison of the workload dimensions was made either prior to the task in a general context or within context of the task just performed. The major findings were that: (1) ModSWAT and UW were more sensitive than TLX to the task demands (i.e., difficulty) of the continuous recognition task; (2) weighting context affected the weights that were assigned the workload dimensions for both TLX and ModSWAT; (3) weighting context did not affect the weighted workload scores; and (4) the weighted and unweighted workload composites were very similar. Results were interpreted within context of averaging across multiple dimensions when several dimensions are insensitive to the task demands. Variability in the weights assigned contributed to the failure to find a effect of weighting.
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Blyth, W. G., i L. J. Marchant. "A Self-weighting Random Sampling Technique". Market Research Society. Journal. 38, nr 4 (lipiec 1996): 1–5. http://dx.doi.org/10.1177/147078539603800411.

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Ying Han, Pang, Andrew Teoh Beng Jin i Lim Heng Siong. "Eigenvector Weighting Function in Face Recognition". Discrete Dynamics in Nature and Society 2011 (2011): 1–15. http://dx.doi.org/10.1155/2011/521935.

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Graph-based subspace learning is a class of dimensionality reduction technique in face recognition. The technique reveals the local manifold structure of face data that hidden in the image space via a linear projection. However, the real world face data may be too complex to measure due to both external imaging noises and the intra-class variations of the face images. Hence, features which are extracted by the graph-based technique could be noisy. An appropriate weight should be imposed to the data features for better data discrimination. In this paper, a piecewise weighting function, known as Eigenvector Weighting Function (EWF), is proposed and implemented in two graph based subspace learning techniques, namely Locality Preserving Projection and Neighbourhood Preserving Embedding. Specifically, the computed projection subspace of the learning approach is decomposed into three partitions: a subspace due to intra-class variations, an intrinsic face subspace, and a subspace which is attributed to imaging noises. Projected data features are weighted differently in these subspaces to emphasize the intrinsic face subspace while penalizing the other two subspaces. Experiments on FERET and FRGC databases are conducted to show the promising performance of the proposed technique.
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Niederlöhner, D., J. Karg, J. Giersch i G. Anton. "The energy weighting technique: measurements and simulations". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 546, nr 1-2 (lipiec 2005): 37–41. http://dx.doi.org/10.1016/j.nima.2005.03.037.

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Imran, Muhammad, Abdul Ghafoor i Victor Sreeram. "Frequency Weighted Model Order Reduction Technique and Error Bounds for Discrete Time Systems". Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/498453.

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Model reduction is a process of approximating higher order original models by comparatively lower order models with reasonable accuracy in order to provide ease in design, modeling and simulation for large complex systems. Generally, model reduction techniques approximate the higher order systems for whole frequency range. However, certain applications (like controller reduction) require frequency weighted approximation, which introduce the concept of using frequency weights in model reduction techniques. Limitations of some existing frequency weighted model reduction techniques include lack of stability of reduced order models (for two sided weighting case) and frequency response error bounds. A new frequency weighted technique for balanced model reduction for discrete time systems is proposed. The proposed technique guarantees stable reduced order models even for the case when two sided weightings are present. Efficient technique for frequency weighted Gramians is also proposed. Results are compared with other existing frequency weighted model reduction techniques for discrete time systems. Moreover, the proposed technique yields frequency response error bounds.
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Moarefi, Alireza, Rateb J. Sweis, Seyyed Mahmoud Hoseini Amiri i Wassim A. AlBalkhy. "Shannon entropy weighting technique as a practical weighting decision-making tool in project management". International Journal of Management Concepts and Philosophy 11, nr 4 (2018): 377. http://dx.doi.org/10.1504/ijmcp.2018.096054.

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Hoseini Amiri, Seyyed Mahmoud, Wassim A. AlBalkhy, Alireza Moarefi i Rateb J. Sweis. "Shannon entropy weighting technique as a practical weighting decision-making tool in project management". International Journal of Management Concepts and Philosophy 11, nr 4 (2018): 377. http://dx.doi.org/10.1504/ijmcp.2018.10017262.

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Zhang, Pengfei, Hong Zhao, Jin Huang, Bingcai Liu i Fen Gao. "Suppression of stitching edge artifacts with weighting technique". Optical Engineering 53, nr 5 (21.05.2014): 054106. http://dx.doi.org/10.1117/1.oe.53.5.054106.

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Lu, George Y., i David W. Wong. "An adaptive inverse-distance weighting spatial interpolation technique". Computers & Geosciences 34, nr 9 (wrzesień 2008): 1044–55. http://dx.doi.org/10.1016/j.cageo.2007.07.010.

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Odu, G. O. "Weighting methods for multi-criteria decision making technique". Journal of Applied Sciences and Environmental Management 23, nr 8 (11.09.2019): 1449. http://dx.doi.org/10.4314/jasem.v23i8.7.

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EL-KHAMY, SAID E., MOHEY M. HADHOUD, MOAWAD I. DESSOUKY, BASSIOUNY M. SALAM i FATHI E. ABD EL-SAMIE. "A SIMPLE ADAPTIVE INTERPOLATION APPROACH BASED ON VARYING IMAGE LOCAL ACTIVITY LEVELS". International Journal of Information Acquisition 03, nr 01 (marzec 2006): 1–8. http://dx.doi.org/10.1142/s0219878906000769.

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In this paper, a simple adaptive interpolation approach is proposed for image interpolation. It depends on modifying the warped distance technique for image interpolation considering the local activity levels in each region of the image. This is performed by weighting the pixels used in the interpolation process with different adaptive weights. The adaptation can be extended to different traditional interpolation techniques such as bilinear, bicubic and cubic spline techniques as well as the warped distance technique. Our study shows that the adaptive weighting of pixels in interpolation yields better results than that obtained using only traditional interpolation methods or by using the warped distance technique. The computation cost of the suggested interpolation approach is moderate and acceptable.
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Bourne, Owen, i Abdul Sattar. "Applying Constraint Weighting to Autonomous Camera Control". Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 1, nr 1 (28.09.2021): 3–8. http://dx.doi.org/10.1609/aiide.v1i1.18707.

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Automating camera control for third-person perspective computer games is a difficult and time-consuming task. One of the challenges games developers confront is how to manage the trade-off between implementation complexity and system usability. In this study, we investigate the application of constraint weighting techniques to the autonomous camera control problem. We demonstrate that this technique can significantly simplify autonomous camera control and reduce the gap between implementation and usability requirements. We describe the use of weighting profiles to control the behaviour of the camera and specialized heuristics for efficiently searching for the solution. We also describe a novel integrated visibility maintenance method. As part of the experimental study, we implemented a 3D game engine that supports dynamic environments; and demonstrate the effectiveness of the use of constraint solving techniques for autonomous camera control problems.
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Krueger, Thomas, i Mark Wrolstad. "Portfolio Allocation Using Free Cash Flows and Other Methods". Journal of Finance Issues 11, nr 2 (31.12.2013): 58–67. http://dx.doi.org/10.58886/jfi.v11i2.2518.

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There are many ways to allocate money invested in shares of common stock within one’s portfolio. The traditional and best known allocation methods are price-weighting, market capitalization-weighting, and equal-weighting. Of these three traditional allocation methods, we find that equally-weighted portfolios performed the best. More recently, attention has been focused on “fundamental weightings” which use financial statement items such as sales, total assets, net income, leverage, EBIT, and free cash flows to weight stock portfolio investments. Using a well-known set of stocks, this research provides insight into the relative advantages of using some of these alternative portfolio allocation methods. This study found that using free cash flows to weight portfolios was the only technique that outperformed equally-weighted portfolios and provided the investor with positive, statistically significant returns. It was also found that when using free cash flows to weight the portfolios, levels of free cash flows were more important that trends.
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Vichianchai, Vuttichai, i Sumonta Kasemvilas. "A New Term Frequency with Gaussian Technique for Text Classification and Sentiment Analysis". Journal of ICT Research and Applications 15, nr 2 (7.10.2021): 152–68. http://dx.doi.org/10.5614/itbj.ict.res.appl.2021.15.2.4.

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This paper proposes a new term frequency with a Gaussian technique (TF-G) to classify the risk of suicide from Thai clinical notes and to perform sentiment analysis based on Thai customer reviews and English tweets of travelers that use US airline services. This research compared TF-G with term weighting techniques based on Thai text classification methods from previous researches, including the bag-of-words (BoW), term frequency (TF), term frequency-inverse document frequency (TF-IDF), and term frequency-inverse corpus document frequency (TF-ICF) techniques. Suicide risk classification and sentiment analysis were performed with the decision tree (DT), naïve Bayes (NB), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) techniques. The experimental results showed that TF-G is appropriate for feature extraction to classify the risk of suicide and to analyze the sentiments of customer reviews and tweets of travelers. The TF-G technique was more accurate than BoW, TF, TF-IDF and TF-ICF for term weighting in Thai suicide risk classification, for term weighting in sentiment analysis of Thai customer reviews for Burger King, Pizza Hut, and Sizzler restaurants, and for the sentiment analysis of English tweets of travelers using US airline services.
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Yuan, Shun, Jing Guo i Xin Zhao. "Integrated Weighting Technique for Coastal Vulnerability to Storm Surges". Journal of Coastal Research 80 (czerwiec 2017): 6–12. http://dx.doi.org/10.2112/si80-002.1.

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Hourali, Samira, Morteza Zahedi i Mansour Fateh. "Coreference Resolution Using Neural MCDM and Fuzzy Weighting Technique". International Journal of Computational Intelligence Systems 13, nr 1 (2020): 56. http://dx.doi.org/10.2991/ijcis.d.200121.001.

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Thangairulappan, Kathirvalavakumar, i Aruna Devi Kanagavel. "Improved Term Weighting Technique for Automatic Web Page Classification". Journal of Intelligent Learning Systems and Applications 08, nr 04 (2016): 63–76. http://dx.doi.org/10.4236/jilsa.2016.84006.

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Lonappan, Linu, Joseph X. Rodrigues, Devika Menon i Lucy J. Gudino. "Improved Magnitude Weighting Technique for Wireless Sensor Network Beamformer". HELIX 10, nr 2 (28.03.2020): 147–54. http://dx.doi.org/10.29042/2020-10-2-147-154.

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Hu, Xiaoping, i Seong-Gi Kim. "A new T2*-weighting technique for magnetic resonance imaging". Magnetic Resonance in Medicine 30, nr 4 (październik 1993): 512–17. http://dx.doi.org/10.1002/mrm.1910300417.

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Nurfariswan, Agi, i Dwi Ardi Wicaksana Putra. "The Classification of Leading Sectors Utilized Weighting Technique Analysis". JEJAK 15, nr 1 (25.03.2022): 63–91. http://dx.doi.org/10.15294/jejak.v15i1.34767.

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Related to the previous studies, there are still questions about what sectors are produced from several economic based approaches each year. This study aims to determine the “very potential” business fields to be developed. This research was led purposively in Sukamara Regency, Kalimantan Tengah Province thinking about that macroeconomic exhibition information actually should be additionally improved. Auxiliary information got by documentation at the Central Statistics Agency, specifically GRDP at 2010 Constant Market Prices for the 2015-2020 period. Arrangement of business fields is done utilizing a weighting come closer from the estimation of Location Quotient, Growth Ratio Model, Sectoral Contribution Percentage and Growth Rate, Shift Share Analysis, and Overlay. The consequences of the review show the pattern of the improvement of the quantity of driving areas that are getting less and less and not in any manner observe any area that is completely equipped for satisfying the normal financial based methodology presumptions consistently. Moreover, the weighting system carried out proposes a new contribution in determining the leading sectors with a clearer classification. Therefore, the results of this study at the same time provide recommendations for the need for an analysis of the leading sector every year as consideration for regional planning.
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Nanda Devita, Lolla Rizky, i Dina Fitrisia Septiarini. "Analisis Kriteria Penetapan Nilai Bagi Hasil Pendanaan Dengan Menggunakan Teknik ANP (Studi Kasus Pada Bank JATIM Syariah)". Jurnal Ekonomi Syariah Teori dan Terapan 3, nr 8 (18.02.2017): 600. http://dx.doi.org/10.20473/vol3iss20168pp600-614.

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The purpose of this study was to find out what is the main criteria in determining revenue sharing value of funding based on interdependence level of internal and external factors by using ANP techniques at Bank Jatim Syariah. The research method used is descriptive qualitative approach with study case method. Data collected by interviews, questionnaires, documentation and other literature. Analysis technique used is the technique of Analytic Network Process (ANP) with weighting questionnaires given to the informant. Weighting is done through comparison between the criteria, sub-criteria and sub-criteria traffic. Results from this study are the criteria of internal factors with sub criteria bank revenue of 0.17416 become a major criterion in the decision-making on determination of revenue sharing value of Funding in Bank Jatim Syariah. Results of the weighting of criteria and sub - criteria through the geometricmean of three informants of Bank Jatim Syariah.
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Krasuski, Kamil, Dariusz Popielarczyk, Adam Ciećko i Janusz Ćwiklak. "A New Strategy for Improving the Accuracy of Aircraft Positioning Using DGPS Technique in Aerial Navigation". Energies 14, nr 15 (22.07.2021): 4431. http://dx.doi.org/10.3390/en14154431.

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In this paper a new mathematical algorithm is proposed to improve the accuracy of DGPS (Differential GPS) positioning using several GNSS (Global Navigation Satellites System) reference stations. The new mathematical algorithm is based on a weighting scheme for the following three criteria: weighting in function of baseline (vector) length, weighting in function of vector length error and weighting in function of the number of tracked GPS (Global Positioning System) satellites for a single baseline. The algorithm of the test method takes into account the linear combination of the weighting coefficients and relates the position errors determined for single baselines. The calculation uses a weighting scheme for three independent baselines denoted as (1A,2A,3A). The proposed research method makes it possible to determine the resultant position errors for ellipsoidal BLh coordinates of the aircraft and significantly improves the accuracy of DGPS positioning. The analysis and evaluation of the new research methodology was checked for data from two flight experiments carried out in Mielec and Dęblin. Based on the calculations performed, it was found that in the flight experiment in Mielec, due to the application of the new research methodology, DGPS positioning accuracy improved from 55 to 94% for all the BLh components. In turn, in the flight experiment in Dęblin, the accuracy of DGPS positioning improved by 63–91%. The study shows that the highest DGPS positioning accuracy is seen when using weighting criterion II, the inverse of the square of the vector length error.
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Bateman, Vesta I., Randall L. Mayes i Thomas G. Carne. "Comparison of Force Reconstruction Methods for a Lumped Mass Beam". Shock and Vibration 4, nr 4 (1997): 231–39. http://dx.doi.org/10.1155/1997/642780.

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Two extensions of the force reconstruction method, the sum of weighted accelerations technique (SWAT), are presented in this article. SWAT requires the use of the structure’s elastic mode shapes for reconstruction of the applied force. Although based on the same theory, the two new techniques do not rely on mode shapes to reconstruct the applied force and may be applied to structures whose mode shapes are not available. One technique uses the measured force and acceleration responses with the rigid body mode shapes to calculate the scalar weighting vector, so the technique is called SWAT-CAL (SWAT using a calibrated force input). The second technique uses the free-decay time response of the structure with the rigid body mode shapes to calculate the scalar weighting vector and is called SWAT-TEEM (SWAT using time eliminated elastic modes). All three methods are used to reconstruct forces for a simple structure.
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PAIKARI, ELHAM, MICHAEL M. RICHTER i GUENTHER RUHE. "DEFECT PREDICTION USING CASE-BASED REASONING: AN ATTRIBUTE WEIGHTING TECHNIQUE BASED UPON SENSITIVITY ANALYSIS IN NEURAL NETWORKS". International Journal of Software Engineering and Knowledge Engineering 22, nr 06 (wrzesień 2012): 747–68. http://dx.doi.org/10.1142/s0218194012400116.

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Software defect prediction is an acknowledged approach used to achieve better product quality and to better utilize resources needed for that purpose. One known method for predicting the number of defects is to apply case-based reasoning (CBR). In this paper, different attribute weighting techniques for CBR-based defect prediction are analyzed. One of the weighting techniques used in this work, Sensitivity Analysis based on Neural Networks (SANN), is based on sensitivity analysis of the impact of attributes as part of neural network analysis. Neural networks are applicable when there are non-linear and complicated relationships among the attributes. Since weighting plays a key role in the CBR model, using an efficient weight calculation method can change the results. The results of SANN are compared with applying uniform weights and weights gained from Multiple Linear Regression (MLR).Evaluation of the accuracy of the overall method for applying the three different weighting techniques is done over five data sets, comprising about 5000 modules from NASA. Two quality measures are applied: Average Absolute Error (AAE) and Average Relative Error (ARE). In addition to the variation of weighting techniques, the impact of varying the number of nearest neighbors is studied.The three main results of the empirical analysis are: (i) In the majority of cases, SANN achieves the most accurate results; (ii) uniform weighting performs better than the MLR-based weighting heuristic; and (iii) there is no significant preference pattern for defining the number of similar objects used for prediction in CBR.
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Lescauskiene, Ingrida, Romualdas Bausys, Edmundas Kazimieras Zavadskas i Birute Juodagalviene. "VASMA Weighting: Survey-Based Criteria Weighting Methodology that Combines ENTROPY and WASPAS-SVNS to Reflect the Psychometric Features of the VAS Scales". Symmetry 12, nr 10 (6.10.2020): 1641. http://dx.doi.org/10.3390/sym12101641.

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Data symmetry and asymmetry might cause difficulties in various areas including criteria weighting approaches. Preference elicitation is an integral part of the multicriteria decision-making process. Weighting approaches differ in terms of accuracy, ease of use, complexity, and theoretical foundations. When the opinions of the wider audience are needed, electronic surveys with the matrix questions consisting of the visual analogue scales (VAS) might be employed as the easily understandable data collection tool. The novel criteria weighting technique VASMA weighting (VAS Matrix for the criteria weighting) is presented in this paper. It respects the psychometric features of the VAS scales and analyzes the uncertainties caused by the survey-based preference elicitation. VASMA weighting integrates WASPAS-SVNS for the determination of the subjective weights and Shannon entropy for the calculation of the objective weights. Numerical example analyzing the importance of the criteria that affect parents’ decisions regarding the choice of the kindergarten institution was performed as the practical application. Comparison of the VASMA weighting and the direct rating (DR) methodologies was done. It revealed that VASMA weighting is able to overcome the main disadvantages of the DR technique—the high biases of the collected data and the low variation of the criteria weights.
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Carramate, L. F. N. D., C. A. B. Oliveira, A. L. M. Silva, A. M. da Silva, J. M. F. dos Santos i J. F. C. A. Veloso. "Energy weighting technique in Quantum Computed Tomography using a MPGD". Journal of Instrumentation 6, nr 02 (4.02.2011): C02002. http://dx.doi.org/10.1088/1748-0221/6/02/c02002.

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Qazi, Aijazahamed, i R. H. Goudar. "An Ontology-based Term Weighting Technique for Web Document Categorization". Procedia Computer Science 133 (2018): 75–81. http://dx.doi.org/10.1016/j.procs.2018.07.010.

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Dirmeyer, Paul A., i Trent W. Ford. "A Technique for Seamless Forecast Construction and Validation from Weather to Monthly Time Scales". Monthly Weather Review 148, nr 9 (12.08.2020): 3589–603. http://dx.doi.org/10.1175/mwr-d-19-0076.1.

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Abstract Seamless prediction means bridging discrete short-term weather forecasts valid at a specific time and time-averaged forecasts at longer periods. Subseasonal predictions span this time range and must contend with this transition. Seamless forecasts and seamless validation methods go hand-in-hand. Time-averaged forecasts often feature a verification window that widens in time with growing forecast leads. Ideally, a smooth transition across daily to monthly time scales would provide true seamlessness—a generalized approach is presented here to accomplish this. We discuss prior attempts to achieve this transition with individual weighting functions before presenting the two-parameter Hill equation as a general weighting function to blend discrete and time-averaged forecasts, achieving seamlessness. The Hill equation can be tuned to specify the lead time at which the discrete forecast loses dominance to time-averaged forecasts, as well as the swiftness of the transition with lead time. For this application, discrete forecasts are defined at any lead time using a Kronecker delta weighting, and any time-averaged weighting approach can be used at longer leads. Time-averaged weighting functions whose averaging window widens with lead time are used. Example applications are shown for deterministic and ensemble forecasts and validation and a variety of validation metrics, along with sensitivities to parameter choices and a discussion of caveats. This technique aims to counterbalance the natural increase in uncertainty with forecast lead. It is not meant to construct forecasts with the highest skill, but to construct forecasts with the highest utility across time scales from weather to subseasonal in a single seamless product.
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Franco, Annie, Neil Malhotra, Gabor Simonovits i L. J. Zigerell. "Developing Standards for Post-Hoc Weighting in Population-Based Survey Experiments". Journal of Experimental Political Science 4, nr 2 (2017): 161–72. http://dx.doi.org/10.1017/xps.2017.2.

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AbstractWeighting techniques are employed to generalize results from survey experiments to populations of theoretical and substantive interest. Although weighting is often viewed as a second-order methodological issue, these adjustment methods invoke untestable assumptions about the nature of sample selection and potential heterogeneity in the treatment effect. Therefore, although weighting is a useful technique in estimating population quantities, it can introduce bias and also be used as a researcher degree of freedom. We review survey experiments published in three major journals from 2000–2015 and find that there are no standard operating procedures for weighting survey experiments. We argue that all survey experiments should report the sample average treatment effect (SATE). Researchers seeking to generalize to a broader population can weight to estimate the population average treatment effect (PATE), but should discuss the construction and application of weights in a detailed and transparent manner given the possibility that weighting can introduce bias.
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ZAKOS, JOHN, i BRIJESH VERMA. "CONCEPT-BASED TERM WEIGHTING FOR WEB INFORMATION RETRIEVAL". International Journal of Computational Intelligence and Applications 06, nr 02 (czerwiec 2006): 193–207. http://dx.doi.org/10.1142/s1469026806001915.

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In this paper we present a novel technique for determining term importance by exploiting concept-based information found in ontologies. Calculating term importance is a significant and fundamental aspect of most information retrieval approaches, and it is traditionally determined through inverse document frequency (IDF). We propose concept-based term weighting (CBW), a technique that is fundamentally different to IDF in that it calculates term importance by intuitively interpreting the conceptual information in ontologies. We show that when CBW is used in an approach for web information retrieval on benchmark data, it performs comparatively to IDF, with only a 3.5% degradation in retrieval accuracy. While this small degradation has been observed, the significance of this technique is that (1) unlike IDF, CBW is independent of document collection statistics, (2) it presents a new way of interpreting ontologies for retrieval, and (3) it introduces an additional source of term importance information that can be used for term weighting.
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Szwargulski, Patryk, Jürgen Rahmer, Mandy Ahlborg, Christian Kaethner i Thorsten M. Buzug. "Experimental evaluation of different weighting schemes in magnetic particle imaging reconstruction". Current Directions in Biomedical Engineering 1, nr 1 (1.09.2015): 206–9. http://dx.doi.org/10.1515/cdbme-2015-0052.

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AbstractMagnetic Particle Imaging (MPI) is a new imaging technique with an outstanding sensitivity, a high temporal and spatial resolution. MPI is based on the excitation and detection of magnetic tracer material by using magnetic fields. The spatial resolution strongly depends on the reconstruction parameters and on the selection and weighting of the system function frequency components. Currently, no fundamental strategy to weight the system function for the reconstruction is given. In this contribution, the influence on the spatial resolution of different selection and weighting methods is analyzed. Thereby, a new strategy is proposed to select and weight the components with respect to their mixing order. As a result, it is confirmed that a weighted system function provides better results of image reconstruction than a non-weighted one. In addition to this, it is shown that the usage of the mixing order in combination with established weightings improves the resolution.
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Anh, Ho Pham Huy. "Real-time identified chaotic plants using neural enhanced learning machine technique". Engineering Computations 38, nr 6 (8.01.2021): 2810–32. http://dx.doi.org/10.1108/ec-01-2020-0049.

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Purpose This paper aims to propose a new neural-based enhanced extreme learning machine (EELM) algorithm, used as an online adaptive estimation model, regarding undetermined system dynamics and containing internal/external perturbations. Design/methodology/approach The EELM structure bases on the single layer feed-forward neural (SLFN) model in which the hidden weighting coefficients are initiated in random and the weighting outputs of the SLFN are online modified using an online adaptive rule implemented from Lyapunov stability concept. Findings Four different benchmark uncertain chaotic system tests have been satisfactorily investigated for demonstrating the superiority of proposed EELM technique. Originality/value Authors confirm that this manuscript is original.
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Hoyle, C., M. Sutcliffe, P. Charlton i S. Mosey. "Limited-angle weighted ultrasonic back-projection imaging with ART algorithm imaging". Insight - Non-Destructive Testing and Condition Monitoring 63, nr 9 (1.09.2021): 534–39. http://dx.doi.org/10.1784/insi.2021.63.9.534.

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Ultrasonic through-transmission data processed using the back-projection algorithm offers depth and lateral information about a defect beyond the capabilities of current through-transmission techniques. This technique was trialled on a carbon steel block containing side-drilled holes. Imaging artefacts can arise from the use of the backprojection algorithm, due to applying a weighting of one to each pixel, irrespective of how much of the pixel is intersected by the beam. Noise can also occur within the image where there are few intersections of the pixels made. This is seen at the edges of the image. In this paper, a novel back-projection technique utilises the weighting of pixels, dependent on the normalised weight of the beam that intersects them, to reduce any artefacts that occurred previously due to the backprojection algorithm. This paper also explores the use of the algebraic reconstruction technique (ART) algorithm for noise removal, thus increasing the sharpness of the defect.
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34

Susanto, Fani, A. Gunawan Santoso i Bagus Abimanyu. "Analisis Pembobotan T2 Turbo Spin Echo (TSE) brain MRI Potongan Axial dengan Penggunaan Sensitivity Encoding (SENSE) dan Tanpa Penggunaan Sense : Evaluasi pada Signal to Noise Ratio (SNR) dan Scan Time". Jurnal Imejing Diagnostik (JImeD) 2, nr 2 (11.07.2016): 148–53. http://dx.doi.org/10.31983/jimed.v2i2.3174.

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Background: On examination brain MRI often finds non-cooperative patients, requiring rapid acquisition techniques. The parallel imaging sensitivity encoding (SENSE) technique utilizes spatial RF coated phased array information to reduce acquisition time by reducing the K space sampling line to produce good quality and spatial resolution, but has a limitation of signal-to-noise ratio (SNR) reduction. SENSE is used with MRI sequence pulses one of them turbo spin echo (TSE). The purpose of this study was to determine the difference of SNR and scan time on TSE T2 weighting brain MRI axial slices between use SENSE and without SENSE.Methods: This research is quantitative study with experimental approach. The data were collected from May to June 2016 at the Radiology Installation of Premier Bintaro Hospital by calculating the SNR through the software for the region of interest (ROI) and calculating the scan time through the scan timer on the workstation monitor. Data analysis was done by statistical test with SPPS 16 application using paired T-test and descriptiveResults: From the result of statistical test, it is known that SNR at TSE T2 weighting between with and without SENSE is obtained p-value 0,000 (p 0, 05). This is because the encoding of the both image are different, On TSE T2 weighting image without SENSE there is the use 1800 pulses approaching the effective TE so the shallow gradient produces maximum echo, while on TSE T2 weighting with SENSE there is a reduction of phase encoding row in K space and the presence of g-factor causes the SNR to decrease. From descriptive analysis result, is known that scan time on TSE T2 weighting between with and without SENSE usage is obtained by reduction of scan time for 1 minute 24 seconds (49, 01%). This is because the acquisition technique between the both image are different, on the TSE T2 weighting without SENSE there is ETL in charging K space, whereas on the TSE T2 Weighting with SENSE there is R-factor causing the sampling not to fill all K space so that scanning time is reduced.Conclusion: There are SNR and scan time differences on TSE T2 weighting brain MRI of the axial slices with SENSE and without SENSE usage.
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Lei, Kin-fong, Péter Baranyi i Yeung Yam. "Complexity Minimalization of Nonsingleton-based Fuzzy-Neural Network". Journal of Advanced Computational Intelligence and Intelligent Informatics 4, nr 4 (20.07.2000): 286–93. http://dx.doi.org/10.20965/jaciii.2000.p0286.

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Singular value based reduction has been proposed for a singleton-based generalized neural network that is general in the sense that singleton-consequent-based fuzzy logic function generators are applied to define nonlinear weighting functions on connections among neurons. The product-sum-gravity inference technique with singleton consequent defines piece-wise linear approximation of nonlinear weighting functions. This paper proposed the use of nonsingleton-consequent-based product-sumgravity fuzzy algorithm that results in a piece-wise nonlinear approximation of weighting functions that considerably improve the approximation properties of the generalized network. This network is called a nonsingleton-based generalized neural network. The main objective of this technical report is to introduce the extension of the singular value based reduction technique to the nonsingleton-based neural network.
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Kianersi, Darius, Suraj Uppalapati, Anirudh Bansal i Jeremy Straub. "Evaluation of a Reputation Management Technique for Autonomous Vehicles". Future Internet 14, nr 2 (19.01.2022): 31. http://dx.doi.org/10.3390/fi14020031.

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Future autonomous vehicles will rely heavily on sharing and communicating information with other vehicles to maximize their efficiency. These interactions, which will likely include details about the positions of surrounding vehicles and obstacles on the road, are essential to their decision-making and the prevention of accidents. However, malicious vehicles—those that intentionally communicate false information—have the capacity to adversely influence other vehicles in the network. This paper presents and evaluates a reputation management system, capable of identifying malicious actors, to mitigate their effects on the vehicle network. The viability of multiple report weighting schemes to calculate reputation is evaluated through a simulation, and a blockchain-based backend for the reputation management system to securely maintain and communicate reputation data is proposed. Storage and computational challenges are considered. This paper shows that weighting schemas, related to the number and reputation of witnesses, positively affect the accuracy of the model and are able to identify malicious vehicles in a network with consistent accuracy and scalability.
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HossainArif, Delwar, A. H M Sofi Ullah, K. M Habibullah i Md Ali Al Mamun. "Personalized Web Recommendation Combining User-centered Collaborative Technique with URL Weighting". International Journal of Computer Applications 63, nr 2 (15.02.2013): 13–18. http://dx.doi.org/10.5120/10437-5116.

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Delavar, Arash Ghorban Niya, i Zahra Jafari. "One Method to Reduce Data Classification Using Weighting Technique in SVM +". Modern Applied Science 10, nr 9 (21.07.2016): 245. http://dx.doi.org/10.5539/mas.v10n9p245.

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SVM, a learning algorithm to analyze data and recognize patterns is used. But there is an important issue, replicate data as well as its real-time processing has not been correctly calculated. For this reason, in this paper we have provided a method DCSVM+ to reduce data classification using weighting technique in SVM +. The proposed method with regard to the parameters to SVM + has the optimum response time. By observing the parameter of data volume and their density, we abled to classify the size of interval as case that this classification to investigated case study reduces the running time of algorithm SVM +. Also by providing objective function of the proposed method, we abled to reduce replicate data to SVM + by integrating parameters and data classification and finally we provided threshold detector (TD) for method of DCSVM + to with respect to the competency function, we reduce the processing time as well as increase data processing speed. Finally proposed algorithm with weighting technique of function to SVM + is optimized in terms of efficiency.
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Rani, Seema, i Manoj Kumar. "Contrast Enhancement using Improved Adaptive Gamma Correction with Weighting Distribution Technique". International Journal of Computer Applications 101, nr 11 (18.09.2014): 47–53. http://dx.doi.org/10.5120/17735-8849.

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Kobayashi, Hirokazu, Ryosuke Tachi i Hisashi Tamaki. "Introduction of a Weighting Factor Setting Technique for Multi-Objective Optimization". Transactions of the Institute of Systems, Control and Information Engineers 31, nr 8 (10.08.2018): 281–94. http://dx.doi.org/10.5687/iscie.31.281.

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Jin, Yadong, Jun Wu, Aimin Yan, Zhijuan Hu, Zhenyu Zhao i Wangzhou Shi. "Optimum beam steering of optical phased arrays using mixed weighting technique". Optik 125, nr 16 (sierpień 2014): 4568–71. http://dx.doi.org/10.1016/j.ijleo.2014.02.004.

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van Til, Janine, Catharina Groothuis-Oudshoorn, Marijke Lieferink, James Dolan i Mireille Goetghebeur. "Does technique matter; a pilot study exploring weighting techniques for a multi-criteria decision support framework". Cost Effectiveness and Resource Allocation 12, nr 1 (2014): 22. http://dx.doi.org/10.1186/1478-7547-12-22.

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Chen, Yuan, Bing Li i Xiao Jun Yang. "An Integrated Fuzzy Multi-Attribute Decision-Making Methodology for Evaluation of Mechanical Product". Key Engineering Materials 450 (listopad 2010): 534–38. http://dx.doi.org/10.4028/www.scientific.net/kem.450.534.

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The concept evaluation of mechanical product is essentially a multi-attribute decision making (MADM) problem in the fuzzy environment. In order to reduce the adverse impact of preference or judgments of decision makers on the final evaluation results, this paper attempts to propose an integrated fuzzy multi-attribute decision making methodology that combines the fuzzy TOPSIS technique and the objective weighting to evaluate mechanical product. The fuzzy TOPSIS technique is applied to rank the design alternatives, and the objective weighting method is integrated into the fuzzy TOPSIS technique to determine the appropriate criteria weights. Finally, a real application to pan mechanism selection for a cooking robot is demonstrated.
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KELLER, ANNETTE, i FRANK KLAWONN. "FUZZY CLUSTERING WITH WEIGHTING OF DATA VARIABLES". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 08, nr 06 (grudzień 2000): 735–46. http://dx.doi.org/10.1142/s0218488500000538.

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We introduce an objective function-based fuzzy clustering technique that assigns one influence parameter to each single data variable for each cluster. Our method is not only suited to detect structures or groups of data that are not uniformly distributed over the structure's single domains, but gives also information about the influence of individual variables on the detected groups. In addition, our approach can be seen as a generalization of the well-known fuzzy c-means clustering algorithm.
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45

Ebert, Tobias, Lars Mewes, Friedrich M. Götz i Thomas Brenner. "Effective Maps, Easily Done: Visualizing Geo-Psychological Differences Using Distance Weights". Advances in Methods and Practices in Psychological Science 5, nr 3 (lipiec 2022): 251524592211018. http://dx.doi.org/10.1177/25152459221101816.

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Psychologists of many subfields are becoming increasingly interested in the geographical distribution of psychological phenomena. An integral part of this new stream of geo-psychological studies is to visualize spatial distributions of psychological phenomena in maps. However, most psychologists are not trained in visualizing spatial data. As a result, almost all existing geo-psychological studies rely on the most basic mapping technique: color-coding disaggregated data (i.e., grouping individuals into predefined spatial units and then mapping out average scores across these spatial units). Although this basic mapping technique is not wrong, it often leaves unleveraged potential to effectively visualize spatial patterns. The aim of this tutorial is to introduce psychologists to an alternative, easy-to-use mapping technique: distance-based weighting (i.e., calculating area estimates that represent distance-weighted averages of all measurement locations). We outline the basic idea of distance-based weighting and explain how to implement this technique so that it is effective for geo-psychological research. Using large-scale mental-health data from the United States ( N = 2,058,249), we empirically demonstrate how distance-based weighting may complement the commonly used basic mapping technique. We provide fully annotated R code and open access to all data used in our analyses.
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Mahajan, Shreya, i Shelly Vadhera. "Plant propagation algorithm for integration of distributed generation in power systems". COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, nr 1 (2.01.2018): 401–17. http://dx.doi.org/10.1108/compel-11-2016-0499.

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Purpose The purpose of this study/paper is to integrate distributed generation optimally in power system using plant propagation algorithm. Distributed generation is a growing concept in the field of electricity generation. It mainly comprises small generation units installed at calculated points of a power system network. The challenge of optimal allocation and sizing of DG is of utmost importance. Design/methodology/approach Plant propagation algorithm and particle swarm optimisation techniques have been implemented where a weighting factor-based multi-objective function is minimised. The objective is to cut down real losses and to improve the voltage profile of the system. Findings The results obtained using plant propagation algorithm technique for IEEE 33-bus systems are compared to those attained using particle swarm optimisation technique. The paper deals with the optimisation of weighting factor-based objective function, which counterpoises the losses and improves the voltage profile of the system and, therefore, helps to deliver the best outcomes. Originality/value This paper fulfils an identified need to study the multi-objective optimisation techniques for integration of distributed generation in the concerned power system network. The paper proposes a novel plant-propagation-algorithm-based technique in appropriate allocation and sizing of distributed generation unit.
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Xing, Xiang, Bainian Liu, Weimin Zhang, Xiaoqun Cao i Jingzhe Sun. "Investigation of Local Weighting Filtering on Randomization Technique Estimates in a Data Assimilation System". Symmetry 13, nr 9 (25.08.2021): 1563. http://dx.doi.org/10.3390/sym13091563.

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Mainstream numerical weather prediction (NWP) centers usually estimate the standard deviations of background error by using a randomization technique to calibrate specific parameters of the background error covariance model in variational data assimilation (VAR) systems. However, the sampling size of the randomization technique is typically several orders of magnitude smaller than that of model state variables, and using finite-sized estimates as a proxy for the truth can lead to sampling noise, which may contaminate the estimation of the standard deviation. The sampling noise is firstly investigated in an atmospheric model to show that the sampling noise has a symmetrical structure oscillating around the truth on a small scale. To alleviate the sampling noise, a heterogeneous local weighting filtering is proposed based on distance-weighted correlation and similarity-weighted correlation. Local weighting filtering is easy to implement in the VAR operational systems and has a low computational cost in the post-processing of reducing the sampling noise. The validity and performance of local weighting filtering method are examined in a realistic model framework to show that the proposed filtering is able to eliminate most of the sampling noise dramatically, the details of the filtered results are more visible, and the accuracy of the filtered results is almost the same as that estimated from the larger sample. The signal-to-noise ratio of the optimal filtered field is improved by nearly 20%. A comparison with the widely used spectral filtering approach in the operational system is considered, showing that the proposed filtering method is more efficient to implement in the filtering procedure and exhibits very good performance in terms of preserving the local anisotropic features of the estimates. These attractive results show the potential efficiency of the local weighting filtering method for solving the noise issue in the randomization technique.
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Ibrahim, Ayad Assad, Ikhlas Mahmoud Farhan i Mohammed Ehasn Safi. "A nonlinearities inverse distance weighting spatial interpolation approach applied to the surface electromyography signal". International Journal of Electrical and Computer Engineering (IJECE) 12, nr 2 (1.04.2022): 1530. http://dx.doi.org/10.11591/ijece.v12i2.pp1530-1539.

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Spatial interpolation of a surface electromyography (sEMG) signal from a set of signals recorded from a multi-electrode array is a challenge in biomedical signal processing. Consequently, it could be useful to increase the electrodes' density in detecting the skeletal muscles' motor units under detection's vacancy. This paper used two types of spatial interpolation methods for estimation: Inverse distance weighted (IDW) and Kriging. Furthermore, a new technique is proposed using a modified nonlinearity formula based on IDW. A set of EMG signals recorded from the noninvasive multi-electrode grid from different types of subjects, sex, age, and type of muscles have been studied when muscles are under regular tension activity. A goodness of fit measure (R2) is used to evaluate the proposed technique. The interpolated signals are compared with the actual signals; the Goodness of fit measure's value is almost 99%, with a processing time of 100msec. The resulting technique is shown to be of high accuracy and matching of spatial interpolated signals to actual signals compared with IDW and Kriging techniques.
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Nsabimana, F. X., V. Subbaraman i U. Zölzer. "A single channel speech enhancement technique exploiting human auditory masking properties". Advances in Radio Science 8 (1.10.2010): 95–99. http://dx.doi.org/10.5194/ars-8-95-2010.

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Abstract. To enhance extreme corrupted speech signals, an Improved Psychoacoustically Motivated Spectral Weighting Rule (IPMSWR) is proposed, that controls the predefined residual noise level by a time-frequency dependent parameter. Unlike conventional Psychoacoustically Motivated Spectral Weighting Rules (PMSWR), the level of the residual noise is here varied throughout the enhanced speech based on the discrimination between the regions with speech presence and speech absence by means of segmental SNR within critical bands. Controlling in such a way the level of the residual noise in the noise only region avoids the unpleasant residual noise perceived at very low SNRs. To derive the gain coefficients, the computation of the masking curve and the estimation of the corrupting noise power are required. Since the clean speech is generally not available for a single channel speech enhancement technique, the rough clean speech components needed to compute the masking curve are here obtained using advanced spectral subtraction techniques. To estimate the corrupting noise, a new technique is employed, that relies on the noise power estimation using rapid adaptation and recursive smoothing principles. The performances of the proposed approach are objectively and subjectively compared to the conventional approaches to highlight the aforementioned improvement.
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Wang, Yan Song, Yue Yan, Zhi Qiu i Jin Zhang. "A Comparison of Psychoacoustical Evaluation Methods for Vehicle Engine Noises Based on Wavelet Shrinkage Denoising Technique". Advanced Materials Research 219-220 (marzec 2011): 93–97. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.93.

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Based on the measured and denoised vehicle engine noises, the sound quality evaluation (SQE) techniques in common use for A-weighting sound pressure level (SPL) and psychoacoustical parameters, such as loudness, sharpness and roughness, are performed and compared in this paper. The wavelet threshold shrinkage method is adopted for sound signal denoising. The comparisons suggest that the A-weighting SPL is not sufficient and can only be used as a reference in vehicle SQE, the psychoacoustical parameters can provide a complete description and more exactly reflect to the subjective feeling of vehicle noises, should be considered in vehicle designs.
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