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Journal articles on the topic 'Artificial orthogonalization'

Author: Grafiati

Published: 30 May 2022

Last updated: 19 July 2025

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1

Robinson, P. John, and A. Saranraj. "Intuitionistic Fuzzy Gram-Schmidt Orthogonalized Artificial Neural Network for Solving MAGDM Problems." Indian Journal Of Science And Technology 17, no. 24 (2024): 2529–37. http://dx.doi.org/10.17485/ijst/v17i24.1386.

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Objectives: To propose a suitable decision-making model based on Intuitionistic Fuzzy sets (IFSs) and Gram-Schmidt orthogonalization process for Artificial Neural Network (ANN). Methods: The IFS data sets appearing in the form of matrices are aggregated using the available aggregation operators in the literature and then the collective aggregated information is processed through Gram-Schmidt orthogonalization for the revised input vectors which is then fed into the ANN algorithm following Delta Learning Rule for the next phase. The weight updation is performed through the ANN and the output is

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2

P, John Robinson, and Saranraj A. "Intuitionistic Fuzzy Gram-Schmidt Orthogonalized Artificial Neural Network for Solving MAGDM Problems." Indian Journal of Science and Technology 17, no. 24 (2024): 2529–37. https://doi.org/10.17485/IJST/v17i24.1386.

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Abstract <strong>Objectives:</strong> To propose a suitable decision-making model based on Intuitionistic Fuzzy sets (IFSs) and Gram-Schmidt orthogonalization process for Artificial Neural Network (ANN). <strong>Methods:</strong> The IFS data sets appearing in the form of matrices are aggregated using the available aggregation operators in the literature and then the collective aggregated information is processed through Gram-Schmidt orthogonalization for the revised input vectors which is then fed into the ANN algorithm following Delta Learning Rule for the next phase. The weig

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3

Bezsonov, O. O., K. O. Oliinyk, O. S. Romanyk, O. G. Rudenko, and N. M. Serdiuk. "Factorized Perseptron Training Algorithms In The Problem Of Constructing A Nonlinear Model." Bionics of Intelligence 1, no. 94 (2020): 23–29. http://dx.doi.org/10.30837/bi.2020.1(94).04.

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In order to improve the computational properties of training procedures for artificial neural networks (ANNs),which, being universal approximators, make it possible to restore any arbitrarily complex continuous nonlinear functionwith a given accuracy, their factorized forms have been developed based on the Cholesky, Householder transformationsand Gram-Schmidt orthogonalization. The analysis of their properties showed that the most effective way to increasethe stability of the learning algorithm is to use the Householder transformation

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Dmitriy, Domin. "ARTIFICIAL ORTHOGONALIZATION IN SEARCHING OF OPTIMAL CONTROL OF TECHNOLOGICAL PROCESSES UNDER UNCERTAINTY CONDITIONS." Eastern-European Journal of Enterprise Technologies 5, no. 9 (65) (2013): 45–53. https://doi.org/10.5281/zenodo.3602372.

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The paper describes further development of the methods of artificial orthogonalization of passive experiment designs describing the experimental values of the output function in a multi-dimensional factor space of a small sample of fuzzy data. This allows fuzzy clustering for the formation of subspaces and further local description of the response function; building local regression equations in the subspaces of full factorial space; calculating the values of the response function at the points of the orthogonalized design of experiment. The methods for processing the asymmetrical design of fa

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Domin, Dmitriy. "Artificial orthogonalization in searching of optimal control of technological processes under uncertainty conditions." Eastern-European Journal of Enterprise Technologies 5, no. 9(65) (2013): 45–53. http://dx.doi.org/10.15587/1729-4061.2013.18452.

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6

Oku, Makito, Takaki Makino, and Kazuyuki Aihara. "Pseudo-Orthogonalization of Memory Patterns for Associative Memory." IEEE Transactions on Neural Networks and Learning Systems 24, no. 11 (2013): 1877–87. http://dx.doi.org/10.1109/tnnls.2013.2268542.

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7

Zeng, Guoqiang, Baihai Zhang, Fenxi Yao, and Senchun Chai. "Modified bidirectional extreme learning machine with Gram–Schmidt orthogonalization method." Neurocomputing 316 (November 2018): 405–14. http://dx.doi.org/10.1016/j.neucom.2018.08.029.

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8

D., Demin. "Application of artificial orthogonalization in search for optimal control of technological processes under uncertainty." Eastern-European Journal of Enterprise Technologies 5, no. 9 (65) (2013): 45–53. https://doi.org/10.15587/1729-4061.2013.18452.

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The aim of research is to develop a methodology for determining the structure and parameters of models that describe technological processes in conditions of uncertainty, which allows finding optimal control at all the main stages of such processes. The object of research is a technological process that can be described by a mathematical model of the "composition - properties" type, which determines the quality of the product at the output of such a process. In this case, the technological process was considered as a generalized concept, a characteristic feature of which is the gener

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9

HAGIWARA, Katsuyuki. "Nonparametric Regression Method Based on Orthogonalization and Thresholding." IEICE Transactions on Information and Systems E94-D, no. 8 (2011): 1610–19. http://dx.doi.org/10.1587/transinf.e94.d.1610.

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Sánchez-Sánchez, Pablo, and Marco A. Arteaga-Pérez. "Improving force tracking control performance in cooperative robots." International Journal of Advanced Robotic Systems 14, no. 4 (2017): 172988141770896. http://dx.doi.org/10.1177/1729881417708969.

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In order to obtain the environment’s information, cooperative robots could need a lot of sensors. A possible solution to reduce the number of sensors might be the use of control–observer structures. In this article, we have designed a control algorithm by using a modified hybrid computed torque method based on the principle of orthogonalization, but in order to avoid the use of tachometers in the implementation, we are including a velocity observer. The stability proof is developed by using the theory of Lyapunov. Simulation of the proposed control structure compared with a well-known control

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11

Samareh-Jahani, Mahsa, Farid Saberi-Movahed, Mahdi Eftekhari, Gholamreza Aghamollaei, and Prayag Tiwari. "Low-Redundant Unsupervised Feature Selection based on Data Structure Learning and Feature Orthogonalization." Expert Systems with Applications 240 (April 2024): 122556. http://dx.doi.org/10.1016/j.eswa.2023.122556.

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12

HIROKAWA, Mariko, and Yoshimitsu KUROKI. "A Fast Implementation of PCA-L1 Using Gram-Schmidt Orthogonalization." IEICE Transactions on Information and Systems E96.D, no. 3 (2013): 559–61. http://dx.doi.org/10.1587/transinf.e96.d.559.

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13

Rhodes, Paul A. "Recoding Patterns of Sensory Input: Higher-Order Features and the Function of Nonlinear Dendritic Trees." Neural Computation 20, no. 8 (2008): 2000–2036. http://dx.doi.org/10.1162/neco.2008.04-07-511.

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Here analytical and simulation results are presented characterizing the recoding arising when overlapping patterns of sensor input impinge on an array of model neurons with branched thresholded dendritic trees. Thus, the neural units employed are intended to capture the integrative behavior of pyramidal cells that sustain isolated Na+ or NMDA spikes in their branches. Given a defined set of sensor vectors, equations were derived for the probability of firing of both branches and neurons and for the expected overlap between the neural firing patterns triggered by two afferent patterns of given

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14

D., Demin, and Sira O. "Estimation of representation of trunned orthogonal subdesigns of the full factor experiment design." System Research & Information Technologies, no. 3 (February 2, 2010): 84–88. https://doi.org/10.5281/zenodo.4275855.

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A generally accepted and widely used approach to solving the problem of analyzing a system of the "composition - property" type consists in identifying and selecting a set of factors that presumably affect the value of a certain response function. Such a function characterizes the efficiency of the system's functioning and is usually formalized in the form of a regression equation that is nonlinear in terms of factors, but linear in terms of parameters. Under the conditions of a large number of influencing factors, it is difficult to solve practical problems of this type due to i

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15

Liu, Wenhao, Hongyuan Wu, Wentao Xiong, et al. "Path Planning for Mobile Robots Based on the Improved DAPF-QRRT* Strategy." Electronics 13, no. 21 (2024): 4233. http://dx.doi.org/10.3390/electronics13214233.

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The rapidly exploring random tree star (RRT*) algorithm is widely used to solve path planning problems. However, the RRT* algorithm and its variants fall short of achieving a balanced consideration of path quality and safety. To address this issue, an improved discretized artificial potential field-QRRT* (IDAPF-QRRT*) path planning strategy is introduced. Initially, the APF method is integrated into the Quick-RRT* (Q-RRT*) algorithm, utilizing the attraction of goal points and the repulsion of obstacles to optimize the tree expansion process, swiftly achieving superior initial solutions. Subse

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Khan, Rabia, and Dushantha Nalin K. Jayakody. "Full Duplex Component-Forward Cooperative Communication for a Secure Wireless Communication System." Electronics 9, no. 12 (2020): 2102. http://dx.doi.org/10.3390/electronics9122102.

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The technological breakthrough in the form of Internet of Things (IoT), Big data and connected world is increasing the demand of better spectrum utilization. Half-Duplex (HD) transmission is mostly used in the earlier communication systems. The high transmission demand requires the better utilization of the existing spectrum. There are several possible ways to overcome the problem of better spectrum usage. In-Band Full Duplex (IBFD) is one of the techniques that can double the Spectral Efficiency (SE) in a Beyond 5G (B5G) communication system. In this paper, our aim is to use the spectral effi

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17

D’Amato, Leo, Gian Luca Lancia, and Giovanni Pezzulo. "The geometry of efficient codes: How rate-distortion trade-offs distort the latent representations of generative models." PLOS Computational Biology 21, no. 5 (2025): e1012952. https://doi.org/10.1371/journal.pcbi.1012952.

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Living organisms rely on internal models of the world to act adaptively. These models, because of resource limitations, cannot encode every detail and hence need to compress information. From a cognitive standpoint, information compression can manifest as a distortion of latent representations, resulting in the emergence of representations that may not accurately reflect the external world or its geometry. Rate-distortion theory formalizes the optimal way to compress information while minimizing such distortions, by considering factors such as capacity limitations, the frequency and the utilit

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18

D., Demin, and Katkova T. "Method for processing a small sample of fuzzy results of an orthogonalized passive experiment." Bulletin of Engineering Academy of Ukraine 2 (February 28, 2010): 234–37. https://doi.org/10.5281/zenodo.4275845.

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The solution of many problems of assessing and predicting the state of complex systems of different nature, operating in a multifactorial environment, is reduced to finding a relationship that connects the values of the monitored parameters of the environment with the value of some resulting parameter – the response characterizing the state of the system. As a mathematical description of such systems, the Kolmogorov-Gabor regression polynomial is often used, the estimates of the coefficients of which are determined by the least squares methods. However, in the case of a small sample of i

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19

Горячая, Вероника Александровна, Михаил Леонидович Угрюмов, Олег Александрович Гайденко, Нина Станиславовна Бакуменко та Ирина Алексеевна Трофимова. "МЕТОД СИНТЕЗУ РІШЕНЬ ЗАДАЧІ ПРОГНОЗУВАННЯ СТАНУ ПАЦІЄНТІВ В СИСТЕМАХ МЕДИЧНОГО МОНІТОРИНГУ". Radioelectronic and Computer Systems, № 3 (12 березня 2019): 68–76. http://dx.doi.org/10.32620/reks.2017.3.08.

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This article proposes a mathematical model and computational method for solutions synthesis to the condition prediction problem of patients in medical monitoring systems. Research describes construction method of diagnostic models for quality criteria assessment of a bio-medical system (BMS) elements condition using monitoring data. Authors show an informativeness (significance) estimation method of the systems diagnosing models variables, obtained based on artificial neural networks (ANN) theory. The article describes a forecasting method of multidimensional time series obtained based on the

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20

Dmitriy, Demin. "STRENGTH ANALYSIS OF LAMELLAR GRAPHITE CAST IRON IN THE «CARBON (C) – CARBON EQUIVALENT (CEQ)» FACTOR SPACE IN THE RANGE OF C = (3,425-3,563) % AND CEQ = (4,214-4,372) %." Technology audit and production reserves 1, no. 1 (33) (2017): 24–32. https://doi.org/10.15587/2312-8372.2017.93178.

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<em>The object of research is the structural lamellar graphite cast iron, where the carbon equivalent (C<sub>eq</sub>) is in the range of (4,214-4,372) % and the carbon content (C) is in the range of (3,425-3,563) %.</em> <em>The aim of research is to describe the distribution of values of tensile strength of cast iron series in the factor space C–C<sub>eq</sub> at a fixed level of Cr-Ni-Cu-Ti alloyed complex in narrow ranges.</em> <em>To achieve this aim, there are the next objectives.</em> <em>1. Build a workable analytical description of the impact of the selected input

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21

Amavasai, Balasundram P., and P. I. Rockett. "Automatic Regularization of Multilayered-Perceptron Training by Weight Orthogonalization." Journal of Intelligent Systems 17, Supplement (2008). http://dx.doi.org/10.1515/jisys.2008.17.s1.57.

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22

Sun, Xu, Xintao Chai, Qingyi Yang, Meiyuan Zhai, and Hanming Gu. "Signal separation using unsupervised learning with local uncorrelated constraints: Applications to ground-roll contaminated data sets." GEOPHYSICS, March 6, 2025, 1–82. https://doi.org/10.1190/geo2024-0447.1.

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Signal/noise separation is a fascinating field in geophysics (e.g., separating ground-roll contaminated shot gathers into ground-roll and other signals, or splitting noisy seismic sections into random noises and noise-free signals). Local orthogonalization (LO) stands out as one of the most intriguing theories initially conceived for random noise attenuation. It postulates that the signal and noise should be orthogonal to each other, implying that they exhibit no correlation. Drawing inspiration from the LO theory and driven by advancements in artificial intelligence (AI) technologies, we inno

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23

Tang, Chen, Qiancheng Yu, Xiaoning Li, Zekun Lu, and Yufan Yang. "Application of DeepForest-CQP multi-factor model in quantitative stock selection." Journal of Intelligent & Fuzzy Systems, January 4, 2022, 1–12. http://dx.doi.org/10.3233/jifs-222328.

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The stock market is a chaotic system, and stock forecasting has been the research focus. This paper proposes a multi-factor model based on DeepForest-CQP to make it more applicable to the stock domain. A t-test is used for selecting factors, and orthogonalization and heteroskedasticity tests are performed for the combined factors, which are particularly important in stock forecasting. DeepForest-CQP was combined with the multi-factor model to construct a stock selection model that can achieve higher returns. The obtained multi-factor quantitative stock selection model is used to study stock se

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24

Brenning, Alexander. "Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification." Machine Learning, April 11, 2023. http://dx.doi.org/10.1007/s10994-023-06327-8.

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AbstractModel-agnostic tools for the post-hoc interpretation of machine-learning models struggle to summarize the joint effects of strongly dependent features in high-dimensional feature spaces, which play an important role in semantic image classification, for example in remote sensing of landcover. This contribution proposes a novel approach that interprets machine-learning models through the lens of feature-space transformations. It can be used to enhance unconditional as well as conditional post-hoc diagnostic tools including partial-dependence plots, accumulated local effects (ALE) plots,

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25

Ravska, Nataliia, Eugene Korbut, Oleksiy Ivanovskyi, et al. "Modified simplified algorithm of the method of group consideration of arguments in simulation processes." International Scientific and Technical conference "The Progressive Technics, Technology and Engineering Education", no. XXII (September 21, 2021). http://dx.doi.org/10.20535/2409-7160.2021.xxii.240466.

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There are many types and methods of simulation, but among them special attention should be paid to methods based on the theory of heuristic self-organization. All algorithms of the method of group argumentation (MGVA) are characterized by structural commonality on the principle of self-organization, which require insignificant requirements for a priori information to search for an infinite number of options. The advantage of the algorithm of the method of group consideration of arguments in comparison with other algorithms of this class is the presence of possibilities of expansion of th

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Zinko, R. "Planning of technical objects and systems." International Scientific and Technical conference "The Progressive Technics, Technology and Engineering Education", no. XXII (September 21, 2021). http://dx.doi.org/10.20535/2409-7160.2021.xxii.240483.

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There are many types and methods of simulation, but among them special attention should be paid to methods based on the theory of heuristic self - organization. All algorithms of the method of group argumentation (MGVA) are characterized by structural commonality on the principle of self - organization, which require insignificant requirements for a priori information to search for an infinite number of options. The advantage of the algorithm of the method of group consideration of arguments in comparison with other algorithms of this class is the presence of possibilities of expansion of the

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27

Qiu, Xun, Yuanyuan Liu, Xiaoqiang Zhang, et al. "Moisture insensitive analysis of polyester/viscose waste textiles using Near-Infrared spectroscopy and Orthogonalization of external parameters algorithm." Journal of Industrial Textiles 53 (January 2023). http://dx.doi.org/10.1177/15280837231187671.

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Near-Infrared (NIR) spectroscopic analyses can be applied in waste textile recycling as a rapid and non-invasive method to provide both qualitative and quantitative results. However, it has been a challenge to enhance the accuracy rate of NIR-based waste textile sorting due to the major influences from water contexts in the samples. Orthogonalization of External Parameters (EPO) has been introduced to reduce the interference from water absorption in NIR spectral signals for better accuracy and reliability in modeling. Here we explore the feasibility of applying EPO strategy with varieties of a

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28

Likun, Liu. "Prediction and Analysis of College Students’ Physical Fitness Test Scores Based on Machine Learning and Neural Network Technology." International Journal of High Speed Electronics and Systems, June 26, 2025. https://doi.org/10.1142/s0129156425407302.

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In this study, a machine learning prediction framework integrating feature engineering optimization is proposed, and an end-to-end intelligent prediction system is constructed to solve the problems of low efficiency of manual calculation and inconsistent standards in traditional physical fitness test performance evaluation. First, principal component analysis (PCA) was used for nonlinear dimensionality reduction of multi-dimensional physiological indicators, and the multicollinearity among parameters such as height, weight and vital capacity was eliminated by feature orthogonalization, and the

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29

Kontorovich, V. "Perspective method for reconfigurable intelligent surface design for NOMA transmission: Theoretical study." Frontiers in Communications and Networks 4 (March 6, 2023). http://dx.doi.org/10.3389/frcmn.2023.1125924.

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The method (paradigm) presented here was inspired by two basic ideas: the assumption of the MIMO-RIS-NOMA communication channel as a dispersive channel with fading, and the representation of the latter by means of the generalized Kronecker channel model (GKCM), applying the “orthogonalization approach” based on utilization of the “universal” eigen basis in the form of prolate spheroidal wave functions (PSWFs). In other words, the essence of the approach is representing the MIMO-RIS-NOMA channel by means of a finite set of artificially created orthogonal trajectories for wave propagation, which

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