Application of a Combined Approach for Predicting a Peptide-Protein Binding Affinity Using Regulatory Regression Methods with Advance Reduction of Features

Murzenko, Oleksandr; Olszewski, Serge; Boskin, Oleg; Lurie, Iryna; Савіна, Наталія; Voronenko, Mariia; Lytvynenko, Volodymyr

doi:10.1109/idaacs.2019.8924244

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…Therefore, when presenting the results that we obtained in this article, it became necessary to use some textual and semantic repetitions of these works. Works [17,18,21,32,36] seemed interesting to us in the context of our research from the point of view of methodology for solving problems. Energy as the driver of any change is such a generalized characteristic of a system that determines its qualitative and quantitative state and causes the transformation of its structure by changing the spatial and temporal arrangement of the elements of the system [39] p. 261.…”

Section: Literature Reviewmentioning

confidence: 99%

Practice Analysis of Effectiveness Components for the System Functioning Process: Energy Aspect

Yarmolenko

Burennikova

Pavlov

et al. 2021

Lecture Notes in Computational Intelligence and Decision Making

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The article presents the author's measuring method for the effectiveness of the functioning processes the system's components based on the models of the efficiency components in terms of the energy approach and reports the applied aspects of its application. The three types of the rates for measurement effectiveness of the processes functioning system' components outlined in previously published author's works, were analyzed. The newest approaches to a method of measurement of newly created authoritative rates for effectiveness of components of process of functioning of system are presented. These approaches are based on the use of the share of profits and cost of processes in total production, and are implemented on the examples of specific industrial enterprises. The technique of approaches differs slightly from the technique used in the examples presented in the previous author's work, making it more accurate. In this sense, innovation lies in the fact that our approaches solve the problem of simultaneous measurement of the efficiency of the system components (using the effectiveness rates of the three indicated types) regardless of the units of measurement of their total, net production and costs, since all this boils down to a dimensionless unit of measurement of the share of benefits and of the share of costs in their total production, moreover, the average values of the effectiveness rates of the functioning of the components of the system to some extent (approximately) can be considered as characteristics of the corresponding rates for the process of the functioning of the system. The examples show the practical implementation of this technology.Keywords: System components • Energy approach • Energy products of the process of the system functioning • Total, clean, cost and scale products of the process • Rates of the effectiveness for process • Scale, effectiveness and efficiency of the process • Models of components of efficiency of Burennikova (Polishchuk) -Yarmolenko

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Section: Literature Reviewmentioning

confidence: 99%

Practice Analysis of Effectiveness Components for the System Functioning Process: Energy Aspect

Yarmolenko

Burennikova

Pavlov

et al. 2021

Lecture Notes in Computational Intelligence and Decision Making

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“…The number of neurons in each of the hidden layers of the current cascade is one of the most important parameters of the network complexity. The recommended number of the hidden layer neurons can be found in [19]. For the case when the degree of non-linearity of neurons is higher than the same degree for synapses, it is allowed to use a higher number of neurons in the hidden layers than the number of inputs.…”

Section: Addition Of a New Network Cascade With The Initial Values Of The Active Cascadementioning

confidence: 99%

“…The zoom level is defined by the number of items which can be displayed on the view without scrolling. The software developed can be used during various data mining tasks [1,3,14,15,19].…”

Section: Principal Component Analysismentioning

confidence: 99%

An Integral Software Solution of the SGTM Neural-Like Structures Implementation for Solving Different Data Mining Tasks

Tkachenko

2021

Lecture Notes in Computational Intelligence and Decision Making

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The paper presents a developed software solution that implements a new learning model and application of artificial neural networks, i.e. the Successive Geometric Transformations Model, to solve various applied data mining tasks. This model is applied to construct Feed Forward Neural Networks, which anticipates the rejection of training goal interpretation as a multi-extremal optimization procedure. The modes of use of the system developed (prediction, time series, and cascade modes) are described in detail and illustrated, as well as the structure and functions of separate constituents of the graphical user interface; data selection and download procedures; neuro-like structure parameterization capabilities for each different mode of operation of the program. Simulation of the developed integral software solution was performed while fulfilling prediction, classification, and time series forecasting. Besides, the feasibility of performing nonlinear PCA analysis at high speed is shown. When performing all the above tasks, the program outcomes are presented in both numerical form and using the appropriate one for a particular mode of visualization in 2D or 3D formats.

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Prediction of Magnetic Remanence of Sm-Co Magnets Using Machine Learning Algorithms

Trostianchyn

Izonin

Tkachenko

et al. 2022

Lecture Notes in Networks and Systems

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Application of a Combined Approach for Predicting a Peptide-Protein Binding Affinity Using Regulatory Regression Methods with Advance Reduction of Features

Cited by 5 publications

References 27 publications

Practice Analysis of Effectiveness Components for the System Functioning Process: Energy Aspect

Practice Analysis of Effectiveness Components for the System Functioning Process: Energy Aspect

An Integral Software Solution of the SGTM Neural-Like Structures Implementation for Solving Different Data Mining Tasks

Prediction of Magnetic Remanence of Sm-Co Magnets Using Machine Learning Algorithms

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