Journal articles: 'Weighted linear combination'

1

Malczewski, Jacek. "Local Weighted Linear Combination." Transactions in GIS 15, no. 4 (August 2011): 439–55. http://dx.doi.org/10.1111/j.1467-9671.2011.01275.x.

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Mukherjee, Jayanta. "Linear combination of weighted t-cost and chamfering weighted distances." Pattern Recognition Letters 40 (April 2014): 72–79. http://dx.doi.org/10.1016/j.patrec.2013.12.012.

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Kang-Sun Choi, A. W. Morales, and Sung-Jea Ko. "Design of linear combination of weighted medians." IEEE Transactions on Signal Processing 49, no. 9 (2001): 1940–52. http://dx.doi.org/10.1109/78.942623.

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Tong, Cezhong, and Ligang Geng. "Linear combination of derivative weighted composition operators." Transactions of Tianjin University 18, no. 1 (January 10, 2012): 69–72. http://dx.doi.org/10.1007/s12209-012-1683-z.

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Oruç, İpek, Laurence T. Maloney, and Michael S. Landy. "Weighted linear cue combination with possibly correlated error." Vision Research 43, no. 23 (October 2003): 2451–68. http://dx.doi.org/10.1016/s0042-6989(03)00435-8.

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Zhang, Li, and Wei-Da Zhou. "Sparse ensembles using weighted combination methods based on linear programming." Pattern Recognition 44, no. 1 (January 2011): 97–106. http://dx.doi.org/10.1016/j.patcog.2010.07.021.

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Carter, Brad, and Claus Rinner. "Locally weighted linear combination in a vector geographic information system." Journal of Geographical Systems 16, no. 3 (November 30, 2013): 343–61. http://dx.doi.org/10.1007/s10109-013-0194-3.

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Guo, Xin, and Maofa Wang. "Compact linear combinations of composition operators over the unit ball." Journal of Operator Theory 88, no. 1 (June 15, 2022): 61–84. http://dx.doi.org/10.7900/jot.2020nov28.2310.

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In this paper, we study the compactness of any finite linear combination of composition operators with general symbols on weighted Bergman spaces over the unit ball in terms of a power type criterion. The strategy of the proof involves the subtle connection of composition operator theory between weighted Bergman spaces and Korenblum spaces.

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Jyh-Rong, Chou. "A weighted linear combination ranking technique for multi-criteria decision analysis." South African Journal of Economic and Management Sciences 16, no. 5 (December 7, 2013): 23–41. http://dx.doi.org/10.4102/sajems.v16i5.639.

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Multi-criteria decision analysis (MCDA) is an alternative approach, which provides a way to systematically structure and analyse complex decision problems. This study presents a novel method of applying the weighted linear combination ranking technique (WLCRT) to MCDA. The proposed WLCRT method is based on the linear combinations of matrix algebra calculations. It has distinct advantages in preference modeling, weight elicitation, and aggregation performance. In this method, the decision matrix of preferences is constructed using a 7-point Likert scale. The weights of criteria are elicited from the proximity matrix of preference relations using the eigenvector method. Then, the weighted generalised means are used to aggregate preference information as well as to rank the order of decision alternatives. The WLCRT method can flexibly reflect different decision attitudes for the decision maker. It is both technically valid and practically useful, and can be used in dealing with multiple criteria analysis problems involving ranking of alternatives.

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Li, Rui, Liang Tao, and Hon Keung Kwan. "Efficient discrete Gabor transform with weighted linear combination of analysis windows." Electronics Letters 52, no. 9 (April 2016): 772–74. http://dx.doi.org/10.1049/el.2015.4143.

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Žgajnar, J., L. Juvančič, and S. Kavčič. "Combination of linear and weighted goal programming with penalty function in optimisation of a daily dairy cow ration." Agricultural Economics (Zemědělská ekonomika) 55, No. 10 (November 9, 2009): 492–500. http://dx.doi.org/10.17221/2601-agricecon.

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The aim of the paper is to present a developed spreadsheet tool for the formulation of a daily dairy cow ration. It is constructed on the basis of two linked sub-models developed on the MS Excel platform. It merges the common linear programming model and the weighted-goal programming model with a penalty function. The first sub-model is included in the tool to make an estimate of the least-cost magnitude that might be expected. The obtained result is entered into the second sub-model as the goal that should be met as closely as possible. The tool was tested at two different values of preferential weights for dairy cows with a 25 kg daily milk yield. The results obtained confirm the benefits of the applied approach. In contrast to the common linear program tools, which terminate at formulation of the least-cost ration, our tool provides more efficient rations (in both economic and nutritive terms) by fine-tuning the nutritive goals and by allowing for harmless deviations from these goals by application of penalty functions.

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Jongkwan Song and Yong Hoon Lee. "Linear combination of weighted order statistic filters: canonical structure and optimal design." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 43, no. 5 (May 1996): 349–62. http://dx.doi.org/10.1109/82.494385.

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Fernández-Vázquez, Esteban, Blanca Moreno, and Geoffrey J. D. Hewings. "A Data-Weighted Prior Estimator for Forecast Combination." Entropy 21, no. 4 (April 23, 2019): 429. http://dx.doi.org/10.3390/e21040429.

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Forecast combination methods reduce the information in a vector of forecasts to a single combined forecast by using a set of combination weights. Although there are several methods, a typical strategy is the use of the simple arithmetic mean to obtain the combined forecast. A priori, the use of this mean could be justified when all the forecasters have had the same performance in the past or when they do not have enough information. In this paper, we explore the possibility of using entropy econometrics as a procedure for combining forecasts that allows to discriminate between bad and good forecasters, even in the situation of little information. With this purpose, the data-weighted prior (DWP) estimator proposed by Golan (2001) is used for forecaster selection and simultaneous parameter estimation in linear statistical models. In particular, we examine the ability of the DWP estimator to effectively select relevant forecasts among all forecasts. We test the accuracy of the proposed model with a simulation exercise and compare its ex ante forecasting performance with other methods used to combine forecasts. The obtained results suggest that the proposed method dominates other combining methods, such as equal-weight averages or ordinal least squares methods, among others.

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El Fidha, Sleh, and Nahla Ben Amor. "On the Use of Linear Combination in PWCP-Nets." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no. 01 (January 31, 2018): 1–26. http://dx.doi.org/10.1142/s0218488518500010.

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Conditional preference networks (CP-nets) are a compact but powerful formalism to represent and reason with qualitative preferences using the notion of conditional preferential independence. However, they suffer from incomparabilities between possible outcomes. Several works have attempted to overcome this weakness by quantifying CP-nets. This paper proposes a new approach combining two of the most interesting extensions of CP-nets, namely Probabilistic CP-nets (PCP-nets) using probability distribution to model uncertainty in different preference statements and Weighted CP-nets (WCP-nets) adding weights to express the relative importance of some attribute values regarding others. The new model so-called PWCP-nets combines the two models by handling both uncertainty and weights. Experimental results show the efficiency of this rich extension of CP-nets compared to PCP-nets and WCP-nets.

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15

Wolf, Elke. "Composition followed by differentiation between weighted Bergman spaces and weighted Banach spaces of holomorphic functions." Acta Universitatis Sapientiae, Mathematica 6, no. 1 (October 1, 2014): 107–16. http://dx.doi.org/10.2478/ausm-2014-0021.

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AbstractLet Φ be an analytic self-map of the open unit disk D in the complex plane. Such a map induces through composition a linear composition operator CΦ: f ↦ f◦Φ.We are interested in the combination of CΦwith the differentiation operator D, that is in the operator DCΦ: f ↦ Φ` · (f ◦ Φ) acting between weighted Bergman spaces and weighted Banach spaces of holomorphic functions

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Wu, Shaomin, and Inma T. Castro. "Maintenance policy for a system with a weighted linear combination of degradation processes." European Journal of Operational Research 280, no. 1 (January 2020): 124–33. http://dx.doi.org/10.1016/j.ejor.2019.06.048.

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17

Mahini, A. Salman, and M. Gholamalifard. "Siting MSW landfills with a weighted linear combination methodology in a GIS environment." International Journal of Environmental Science & Technology 3, no. 4 (September 2006): 435–45. http://dx.doi.org/10.1007/bf03325953.

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18

Silva-Gallegos, Juan José, Carlos Arturo Aguirre-Salado, Liliana Miranda-Aragón, Guillermo Sánchez-Díaz, José René Valdez-Lazalde, José Walter Pedroza-Carneiro, and Jorge Alberto Flores-Cano. "Locating Potential Zones for Cultivating Stevia rebaudiana in Mexico: Weighted Linear Combination Approach." Sugar Tech 19, no. 2 (April 18, 2016): 206–18. http://dx.doi.org/10.1007/s12355-016-0446-x.

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Akopyan, Arsenyi, and Herbert Edelsbrunner. "The Weighted Gaussian Curvature Derivative of a Space-Filling Diagram." Computational and Mathematical Biophysics 8, no. 1 (August 12, 2020): 74–88. http://dx.doi.org/10.1515/cmb-2020-0101.

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AbstractThe morphometric approach [11, 14] writes the solvation free energy as a linear combination of weighted versions of the volume, area, mean curvature, and Gaussian curvature of the space-filling diagram. We give a formula for the derivative of the weighted Gaussian curvature. Together with the derivatives of the weighted volume in [7], the weighted area in [4], and the weighted mean curvature in [1], this yields the derivative of the morphometric expression of solvation free energy.

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KALTCHENKO, ALEXEI, NINA TIMOFEEVA, and EUGENIY A. TIMOFEEV. "BIAS REDUCTION OF THE NEAREST NEIGHBOR ENTROPY ESTIMATOR." International Journal of Bifurcation and Chaos 18, no. 12 (December 2008): 3781–87. http://dx.doi.org/10.1142/s0218127408022731.

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A new family of entropy estimators, constructed as a linear combination (weighted average) of nearest neighbor estimators with slightly different individual properties, is proposed. It is shown that a special suboptimal selection of the coefficients in the linear combination results in a polynomial reduction of the estimator's bias, which continues the line of work of P. Grassberger on entropy estimation. Computer simulation results are provided.

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21

Ponnaian, Devaraj. "Some remarks on reconstruction from local weighted averages." Tamkang Journal of Mathematics 44, no. 3 (September 21, 2012): 217–26. http://dx.doi.org/10.5556/j.tkjm.44.2013.820.

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We solve the convolution equation of the type $f\star\mu=g,$ where $f\star \mu$ is the convolution of $f$ and $\mu$ defined by $(f\star \mu)(x)=\int_{{\mathbb{R}}}f(x-y)d\mu(y),$ $g$ is a given function and $\mu$ is a finite linear combination of translates of an indicator function on an interval.

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Sathiyaraj, Chinnasamy, M. Ramachandran, Ramu Kurinjimalar, Selvam Manjula, and Soundhraj Sowmiya. "Exploring the Possibility of Urban Agriculture Farn." Agricultural, Biologicals and Food Science 1, no. 1 (June 1, 2022): 1–8. http://dx.doi.org/10.46632/abfs/1/1/1.

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In this paper we used WPM method; it is a unique combination of weight sum model and weight product model. Due to its mathematical simplicity and ability to deliver more Compared with WSM and WPM Accurate results. As an effective decision-making tool Now widely accepted methods. In decision-making theory, Weighted Sum Model (WSM), Weighted Linear Combination (WLC) or Also known as Simple Admission Waiting (SAW) is used to evaluate multiple alternatives based on a list of weighted objectives (WOT) criteria used to rank different alternatives. Weighted linear composition is an analytical method used when making multiple attribute decisions (MADM) or considering multiple attributes. The weighted average is the average type calculated by multiplying the weight (or probability) associated with a particular event or effect by its relative magnitude effect. The WPM methods is the most ideal solution Short-distance and negative-best the solution with the longest distance from the solution Determines, but the comparison of these distances Does not consider importance. From the result it is seen that Salem is got the first rank whereas is the Madurai is having the lowest rank.

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Hobeichi, Sanaa, Gab Abramowitz, Jason Evans, and Anna Ukkola. "Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate." Hydrology and Earth System Sciences 22, no. 2 (February 21, 2018): 1317–36. http://dx.doi.org/10.5194/hess-22-1317-2018.

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Abstract. Accurate global gridded estimates of evapotranspiration (ET) are key to understanding water and energy budgets, in addition to being required for model evaluation. Several gridded ET products have already been developed which differ in their data requirements, the approaches used to derive them and their estimates, yet it is not clear which provides the most reliable estimates. This paper presents a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000–2009. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. The weighting method is based on a technique that provides an analytically optimal linear combination of ET products compared to site data and accounts for both the performance differences and error covariance between the participating ET products. We examine the performance of the weighting approach in several in-sample and out-of-sample tests that confirm that point-based estimates of flux towers provide information on the grid scale of these products. We also provide evidence that the weighted product performs better than its six constituent ET product members in four common metrics. Uncertainty in the ET estimate is derived by rescaling the spread of participating ET products so that their spread reflects the ability of the weighted mean estimate to match flux tower data. While issues in observational data and any common biases in participating ET datasets are limitations to the success of this approach, future datasets can easily be incorporated and enhance the derived product.

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Baskurt, Zeki Mehmet, and Cevdet Coskun Aydin. "Nuclear power plant site selection by Weighted Linear Combination in GIS environment, Edirne, Turkey." Progress in Nuclear Energy 104 (April 2018): 85–101. http://dx.doi.org/10.1016/j.pnucene.2017.09.004.

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Tsuchida, Masaru, Takahito Kawanishi, Hiroshi Murase, and Shigeru Takagi. "Joint Audio-Visual Tracking Based on Dynamically Weighted Linear Combination of Probability State Density." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 2 (March 20, 2004): 190–99. http://dx.doi.org/10.20965/jaciii.2004.p0190.

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This paper proposes a method that can be applied to speaker tracking under stabilized, continuous conditions using visual and audio information even when input information is interrupted due to disturbance or occlusion caused by the effects of noise or varying illumination. Using this method, the position of a speaker is expressed based on a likelihood distribution that is obtained through integration of visual information and audio information. First, visual and audio information is integrated as as a weighted linear combination of probability density distribution, which is estimated as a result of the observation of the visual and audio information. In this case, the weight is taken as a variable, which varys in proportion to the maximum value of probability density distributions obtained for each type of information. Next, the result obtained as described above and the weighted linear combination of the distribution in the past are obtained, and the result thus obtained is taken as the likelihood distribution related to the position of the speaker. By changing the weight dynamically, it becomes possible to select the type of information freely or to add weight and, accordingly, to conduct stabilized, continuous tracking even when the speaker cannot be detected momentarily due to occlusion, voice interruption, or noise. We conducted a series of experiments on speaker tracking using circular microphone array and an omni-directional camera. In this way, we have succeeded in confirming it possible to perform stabilized tracking on speakers continuously in spite of occlusion or voice interruption.

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Bai, Quan Yong. "Urban Planning Development in Complex Combination Networks." Applied Mechanics and Materials 295-298 (February 2013): 2528–34. http://dx.doi.org/10.4028/www.scientific.net/amm.295-298.2528.

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In this paper, we proposed some applied research methods about Chinese urban economic development in complex combination networks, such as the economy force and economy growth momentum in general non-linear economy force control system, general synergetic structure theory, Steiner minimum weighted networks, and economics scale degree. These research methods were applied to illustrate and analyze Chinese urban economic phenomena with Ising model in complex combination networks, which helped us to understand Chinese economic problems better and made some suggestions for urban economic development.

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Di, Hong Wei, Kai Han Zhang, and Hui Gao. "Adaptive Video Denoising Based on Spatio-Temporal Combination." Applied Mechanics and Materials 321-324 (June 2013): 1230–33. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1230.

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An algorithm of adaptive video denoising base on spatio-temporal combination is demonstrated. The adaptive threshold function is obtained through unary linear regression analysis combining interval estimation and hypothesis test. By motion detection to multi-frame images, still regions and motion regions of video image are distinguished through the adaptive threshold. Temporal weighted average filter to the still regions and spatial ANL filter to the motion regions are used separately. Experimental results show that the proposed algorithm works well.

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Seoh, Munsup, and Madan L. Puri. "Asymptotic Normality of a Class of Nonparametric Statistics." Econometric Theory 3, no. 3 (June 1987): 313–47. http://dx.doi.org/10.1017/s0266466600010422.

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Asymptotic normality is established for a class of statistics which includes as special cases weighted sum of independent and identically distributed (i.i.d.) random variables, unsigned linear rank statistics, signed rank statistics, linear combination of functions of order statistics, and linear function of concomitants of order statistics. The results obtained unify as well as extend a number of known results.

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Hongcong, Liu. "Time Series Forecasting as a Measure." International Journal of Advanced Pervasive and Ubiquitous Computing 5, no. 2 (April 2013): 47–55. http://dx.doi.org/10.4018/japuc.2013040105.

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In this paper, the time series prediction is as a measure. At the same time, the optimal combination forecast using each method can be defined as the actual impact measurement value of true. Effect of its theoretical estimation has error correlation coefficient values. The optimal weighted linear combination is the theoretical prediction which can be proved, also, simple averaging method is linear combination forecasting optimal weights. Especially, based on the robust statistic theory, the mathematical derivation and numerical tests on the superiority is simple.

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Li, Xiangyu, Tianjie Lei, Jing Qin, Jiabao Wang, Weiwei Wang, Dongpan Chen, Guansheng Qian, and Jingxuan Lu. "An Improved Combination Model for the Multi-Scale Prediction of Slope Deformation." Water 14, no. 22 (November 14, 2022): 3667. http://dx.doi.org/10.3390/w14223667.

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Slope collapse is one of the most severe natural disaster threats, and accurately predicting slope deformation is important to avoid the occurrence of disaster. However, the single prediction model has some problems, such as poor stability, lower accuracy and data fluctuation. Obviously, it is necessary to establish a combination model to accurately predict slope deformation. Here, we used the GFW-Fisher optimal segmentation method to establish a multi-scale prediction combination model. Our results indicated that the determination coefficient of linear combination model, weighted geometric average model, and weighted harmonic average model was the highest at the surface spatial scale with a large scale, and their determination coefficients were 0.95, 0.95, and 0.96, respectively. Meanwhile, RMSE, MAE and Relative error were used as indicators to evaluate accuracy and the evaluation accuracy of the weighted harmonic average model was the most obvious, with an accuracy of 5.57%, 3.11% and 3.98%, respectively. Therefore, it is necessary to choose the weighted harmonic average model at the surface scale with a large scale as the slope deformation prediction combination model. Meanwhile, our results effectively solve the problems of the prediction results caused by the single model and data fluctuation and provide a reference for the prediction of slope deformation.

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Grüner, Hans Peter, and Thomas Tröger. "Linear Voting Rules." Econometrica 87, no. 6 (2019): 2037–77. http://dx.doi.org/10.3982/ecta16004.

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How should a society choose between two social alternatives if participation in the decision process is voluntary and costly, and monetary transfers are not feasible? Assuming symmetric independent private values, we show that it is utilitarian‐optimal to use a linear voting rule: votes get alternative‐dependent weights, and a default obtains if the weighted sum of votes stays below some threshold. Any combination of weights and threshold can be optimal. A standard quorum rule can be optimal only when it yields the same outcome as a linear rule. A linear rule is called upper linear if the default is upset at every election result that meets the threshold exactly. We develop a perturbation method to characterize equilibria of voting rules in the case of small participation costs and show that leaving participation voluntary increases welfare for any two‐sided upper linear rule that is optimal under compulsory participation.

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HUANG, JIAN, PONGCHI YUEN, WEN-SHENG CHEN, JIANHUANG LAI, and XINGE YOU. "LINEAR AND NONLINEAR FEATURE-BASED FUSION ALGORITHMS FOR FACE RECOGNITION." International Journal of Wavelets, Multiresolution and Information Processing 04, no. 04 (December 2006): 659–76. http://dx.doi.org/10.1142/s021969130600152x.

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Integration of various face recognition algorithms has proved to be a feasible approach to improve the performance of a face recognition system. Different face recognition algorithms are often based on different representations of the input patterns or on extracted features and hence may complement each other. Linear and nonlinear feature based algorithms can capture and handle different kinds of variations, such as pose, illumination and expression variations. To make full use of the different advantages of different classifiers, we propose combining four linear and nonlinear face recognition algorithms via a weighted combination scheme to improve the recognition performance of a face recognition system. The FERET, YaleB and CMU PIE database are used for evaluating the combination scheme and the results confirm the effectiveness of the proposed combination scheme.

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Lee, Jeong. "Price Dependencies and Investors’ Choice." Journal of Finance Issues 11, no. 1 (June 30, 2013): 26–32. http://dx.doi.org/10.58886/jfi.v11i1.2508.

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Under the efficient market hypothesis, where many investors resort to “buy and hold” strategies with maximum diversifications, “capitalization-weighted indexation” may offer investors the best risk-return combination. But the existence of non-linear dependences shows that prices of securities may be subject to temporary shocks that obscure their true value. In this case, “fundamental indexation” may achieve returns superior to the capitalization-weighted indexation.

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Asadi, Yasaman, Najmeh Neysani Samany, Majid Kiavarz Moqadam, Ata Abdollahi Kakroodi, and Meysam Argany. "Seismic vulnerability assessment of urban buildings using the rough set theory and weighted linear combination." Journal of Mountain Science 19, no. 3 (February 21, 2022): 849–61. http://dx.doi.org/10.1007/s11629-021-6724-4.

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Kang, Je-Won. "Adaptive Residual DPCM using Weighted Linear Combination of Adjacent Residues in Screen Content Video Coding." Journal of Broadcast Engineering 20, no. 5 (September 30, 2015): 782–85. http://dx.doi.org/10.5909/jbe.2015.20.5.78.

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Prišenk, Jernej, Jožef Vincec, Lazar Pavic, Crtomir Rozman, Jernej Turk, and Karmen Pažek. "Cropping-Plan Optimization on Agricultural Holdings with a Combination of Linear and Weighted-goal Programming." Applied Engineering in Agriculture 35, no. 1 (2019): 109–16. http://dx.doi.org/10.13031/aea.13138.

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Abstract.We present a crop plan that aims to maximize farmers’ returns and minimize production costs for the analyzed agricultural holding. This study describes a model that combines linear programming (LP) and the weighted goal programming (WGP) method with penalty functions to simultaneously satisfy a variety of goals within the tolerance interval bounds in terms of their weights. The results indicate that, from an economic perspective, WGP sub-model including LP gives a better solution than using the LP sub-model separately. We designed the model to handle five different types of field and vegetable crops during crop planning and was tested for WGP optimization [WGPSC1, WGPSC2, WGPSC3, and WGPSC4 (SC4 for testing model parameterization)) on four different scenarios. For example, the farmers’ returns in the WGP scenarios were higher or equal as in LP scenario (by approx. €100 to €110) while the costs were reduced (from €2.58 in the case of mechanical labor costs and to €1,376.66 for fertilizer costs). In addition, the combination of both serves as a more viable option for diversified and economically optimized crops to be included in crop plans. It is also important that the WGP calculated higher farmer returns, even though it was run on a cropping area that was 0.02 ha smaller than that in the LP. Further, the model was tested with a parameterization process to determine and explain the role of weights and penalty functions on the quality of the model results. Keywords: Agricultural application, Agricultural economics, Farmer’s return, Mathematical modelling.

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Wang, Chang, Fei Qi, Guangming Shi, and Jingbo Ren. "A linear combination-based weighted least square approach for target localization with noisy range measurements." Signal Processing 94 (January 2014): 202–11. http://dx.doi.org/10.1016/j.sigpro.2013.06.005.

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Malczewski, Jacek. "On the Use of Weighted Linear Combination Method in GIS: Common and Best Practice Approaches." Transactions in GIS 4, no. 1 (January 2000): 5–22. http://dx.doi.org/10.1111/1467-9671.00035.

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Akopyan, Arsenyi, and Herbert Edelsbrunner. "The Weighted Mean Curvature Derivative of a Space-Filling Diagram." Computational and Mathematical Biophysics 8, no. 1 (July 27, 2020): 51–67. http://dx.doi.org/10.1515/cmb-2020-0100.

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AbstractRepresenting an atom by a solid sphere in 3-dimensional Euclidean space, we get the space-filling diagram of a molecule by taking the union. Molecular dynamics simulates its motion subject to bonds and other forces, including the solvation free energy. The morphometric approach [12, 17] writes the latter as a linear combination of weighted versions of the volume, area, mean curvature, and Gaussian curvature of the space-filling diagram. We give a formula for the derivative of the weighted mean curvature. Together with the derivatives of the weighted volume in [7], the weighted area in [3], and the weighted Gaussian curvature [1], this yields the derivative of the morphometric expression of the solvation free energy.

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Pincheira-Brown, Pablo, Andrea Bentancor, and Nicolás Hardy. "An Inconvenient Truth about Forecast Combinations." Mathematics 11, no. 18 (September 5, 2023): 3806. http://dx.doi.org/10.3390/math11183806.

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It is well-known that the weighted averages of two competing forecasts may reduce mean squared prediction errors (MSPE) and may also introduce certain inefficiencies. In this paper, we take an in-depth view of one particular type of inefficiency stemming from simple combination schemes: Mincer and Zarnowitz inefficiency or auto-inefficiency for short. Under mild assumptions, we show that linear convex forecast combinations are almost always auto-inefficient, and, therefore, greater reductions in MSPE are almost always possible. In particular, we show that the process of taking averages of forecasts may induce inefficiencies in the combination, even when individual forecasts are efficient. Furthermore, we show that the so-called “optimal weighted average” traditionally presented in the literature may indeed be inefficient as well. Finally, we illustrate our findings with simulations and an empirical application in the context of the combination of headline inflation forecasts for eight European economies. Overall, our results indicate that in situations in which a number of different forecasts are available, the combination of all of them should not be the last step taken in the search of forecast accuracy. Attempts to take advantage of potential inefficiencies stemming from the combination process should also be considered.

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Hosseini, Seyed Ata Ollah, Parisa Moghadasi, and Asghar Fallah. "Forest Road Network Design based on Multipurpose Forestry Management in Hyrcanian Forest." Journal of Environmental Science and Management 22, no. 2 (December 29, 2019): 13–20. http://dx.doi.org/10.47125/jesam/2019_2/03.

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Traditionally, the main focus of forestry management has been based on wood production but more recently it is directed at multifunctional forest management. Multifunctional forestry management includes many considerations such as ecotourism, ecology, economic and social issues of forest dwellers as well as wood production. This study aims to design forest roads using GIS and satellite data of SPOT-HRG in the Darabkla forest based on Multipurpose Forestry. The study used the multi-criteria evaluation method based on fuzzy logic to assess the potential of land area for a road network. Opinions of experts and scholars were used to select four criteria and 18 sub-criteria for road design. Analytical Hierarchy Process (AHP) was used for weighting factors. Layers were combined using a weighted linear combination (WLC) operator and the map of crossing the road potential was identified and zoned. The road was designed using the PEGGER program. Geographic Information System (GIS) and satellite data of SPOT-HRG were effective tools for improving outcomes. Weighted Linear Combination (WLC) Model for combination layers was used in this study and recommended the multi object operation (MOLA) in future studies.

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Omidi, Katayoun, Afsaneh Afzali, Hossein Vahidi, and Sheida Mahnam. "Ranking of Suitable Areas for Establishing Industries in Kashan City Using VIKOR and TOPSIS Methods in Fuzzy Environment." Journal of Advances in Environmental Health Research 10, no. 2 (April 1, 2022): 133–48. http://dx.doi.org/10.32598/jaehr.10.2.1241.

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Background: In this research, among the Multi Criteria Decision Making (MCDM) methods, a combination of VIKOR and TOPSIS methods with fuzzy set theory was used to overcome the uncertainty in the ranking of alternatives. The purpose of this paper was to locate the industries of Kashan City and rank the appropriate alternatives using analytic hierarchical process (AHP) and the prioritization methods of fuzzy VIKOR and fuzzy TOPSIS. Methods: In this study, first, the effective criteria in GIS (Geographic Information System) were examined and standardized according to fuzzy logic. Then, by presenting expert opinion through AHP, the criteria were weighted, and in order to determine suitable places for establishing industries, according to the required minimum area, six alternatives were extracted from the weighted linear combination method. Subsequently, the alternatives were ranked using fuzzy VIKOR and fuzzy TOPSIS methods. The sensitivity analysis was performed in the fuzzy TOPSIS method by shifting the criteria weights and producing different weighting scenarios. The fuzzy VIKOR method was analyzed for different values of the υ variable. Results: Weighting of criteria by AHP showed that the distance from surface water with a weight coefficient of 0.200 was the most important one. according to the required minimum area, six alternatives were extracted from the weighted linear combination method. Conclusion: The sensitivity analysis of both methods showed that 405 hectares in the Southeast of Kashan are the best ones to establish industries.

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Panwar, Darsha, Manoj Jha, and Namita Srivastava. "Optimization of Risk and Return Using Fuzzy Multiobjective Linear Programming." Advances in Fuzzy Systems 2018 (September 3, 2018): 1–9. http://dx.doi.org/10.1155/2018/4279236.

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Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering a combination of several methodologies for portfolio selection, such as investor topology, cluster analysis, and the analytical hierarchy process (AHP) to facilitate ranking the assets and fuzzy multiobjective linear programming (FMOLP). This paper considers some important factors of stock, like relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), and price to earnings growth ratio (PEG ratio), apart from the risk and return and stocks which are included within these same factors. Employing fuzzy multiobjective linear programming, optimization is performed using seven objective functions viz., return, risk, relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), price to earnings growth ratio (PEG ratio), and AHP weighted score. The FMOLP transforms the multiobjective problem to a single objective problem using the “weighted adaptive approach” in which the weights are calculated by AHP or choices by the investors. The FMOLP model permits choices in solution.

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Lin, Hao, Cheng He, and Yixun Lin. "Bicriteria scheduling for due date assignment with total weighted tardiness." RAIRO - Operations Research 52, no. 2 (April 2018): 359–70. http://dx.doi.org/10.1051/ro/2017074.

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In the due date assignment, the bicriteria scheduling models are motivated by the trade-off between the due date assignment cost and a performance criterion of the scheduling system. The bicriteria scheduling models related to the maximum tardiness and the weighted number of tardy jobs have been studied in the literature. In this paper we consider a new model with criteria of the due date assignment cost and the total weighted tardiness. The main results are polynomial-time algorithms for the linear combination version, the constraint version, and the Pareto optimization version of bicriteria scheduling.

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Arif, Muhammad, Miraj Ul Haq, and Jin-Lin Liu. "A Subfamily of Univalent Functions Associated with q-Analogue of Noor Integral Operator." Journal of Function Spaces 2018 (2018): 1–5. http://dx.doi.org/10.1155/2018/3818915.

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The main objective of the present paper is to define a new subfamily of analytic functions using subordinations along with the newly defined q-Noor integral operator. We investigate a number of useful properties such as coefficient estimates, integral representation, linear combination, weighted and arithmetic means, and radius of starlikeness for this class.

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Hu, Tao, Xisheng Li, and Jia You. "The weighted fusion prediction algorithm of acoustic interval optimized by PCA-PSO-BP and MLRM." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012004. http://dx.doi.org/10.1088/1742-6596/2258/1/012004.

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Abstract Acoustic interval is widely used in drilling operation, but the actual drilling operation is limited by well depth, geological conditions and economic cost, so it is difficult to directly measure the value of acoustic interval. A model between logging data and acoustic interval can be constructed to predict acoustic interval. In view of the shortcomings of traditional algorithms, this paper proposes a weighted fusion algorithm based on the combination optimization of the PCA, PSO, BP and MLRM, carries out the PCA and PSO combination optimization the BP prediction for non-linear logging data, the MLRM regression prediction for linear logging data, and then weights and fuses two groups of prediction results to obtain the final result. Through the test and comparison of several groups of logging data experimental results, the prediction effect of the fusion algorithm is better than the BP, and the prediction effect of the PCA and the PSO optimized the BP verifies the feasibility of the fusion algorithm proposed in this paper.

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Mada, Grandianus Seda, Nugraha K. F. Dethan, Fried Markus Allung Blegur, and Adriano Dos Santos. "WEIGHTED ADDITIVE MODEL AND CHANCE CONSTRAINED TECHNIQUE FOR SOLVING NONSYMMETRICAL STOCHASTIC FUZZY MULTIOBJECTIVE LINEAR PROGRAM." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 1 (March 21, 2022): 293–304. http://dx.doi.org/10.30598/barekengvol16iss1pp291-302.

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The problems of linear programming are developing from time to time, and its complexity is constantly growing. Various problems can be viewed as a multi-objective fuzzy linear programming, multi-objective stochastic linear programming or a combination of both. This research is focused on examining Multi-Objective Fuzzy Stochastic Linear Programming (MOFSLP) with each of the objective functions has a different level of importance to decision makers, or better known as the nonsymmetrical model. The objective function of the linear program contains fuzzy parameters, while the constraint function contains the fuzzy parameters and random variables. The purpose of this study is to develop an algorithm to transform the MOFSLP be a Program of linear Single-Objective Deterministic Linear Programming (SODLP) so that it can be solved using simplex method. In the process of transforming MOFSLP to SODLP, several approaches have been used. They are; weighted additive model, analytic hierarchy process and chance constrained technique. An example of numerical computations has been provided at the end of the discussion in order to illustrate how the algorithm works. The resulted Model and algorithm are expected to help companies in the decision making process.

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Chen, Wei, Hongxing Han, Bin Huang, Qile Huang, and Xudong Fu. "Variable-Weighted Linear Combination Model for Landslide Susceptibility Mapping: Case Study in the Shennongjia Forestry District, China." ISPRS International Journal of Geo-Information 6, no. 11 (November 7, 2017): 347. http://dx.doi.org/10.3390/ijgi6110347.

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Zhou, J., M. A. Georgeson, and R. F. Hess. "Linear binocular combination of responses to contrast modulation: Contrast-weighted summation in first- and second-order vision." Journal of Vision 14, no. 13 (November 25, 2014): 24. http://dx.doi.org/10.1167/14.13.24.

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Huang, Chao, Fei Gao, and Hongyan Jiang. "Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/538594.

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Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA) and grey relational analysis (GRA). Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM) is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM) in China shows that the proposed approach has good performance.

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Journal articles on the topic 'Weighted linear combination'

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