DEVELOPMENT OF A DATABASE STRUCTURE FOR STORING MODELS FOR DETERMINATED ALPHABETES CLASSES RECOGNITION BASED ON THE SET OF HETEROGENEOUS CHARACTERISTIC
DOI:
https://doi.org/10.20998/2079-0023.2019.02.09Keywords:
objects and situations recognition system, recognisation systems software, recognisation process model representation, structure database for store quantitative and qualitative characteristicAbstract
The objects and situations recognition is important problem in such areas as the definition of the types of air objects according to various sources of information, diagnosis of patients on the results of the survey and analysis, diagnostics of different equipment or technic types. Under the recognition refers to the process of obtaining the initial information about the affiliation of each studied element to a class based on analyze of the incoming information about studied elements of the environment, using methods to transform input data environment into output. The paper presents a model of the recognition process, which is characterized by the decision making of the class object based on the analysis of a set of quantitative and qualitative characteristics of which information can be obtained from various sources. The article presents a formalized set-theoretic model of the recognition process. According to the model, to attribute an object or situation to a certain class, it is necessary to define a set of feature groups of different types that allow to identify objects (situations) of a particular class. To perform recognition process experts based on experience or on the basis of statistical data must define a fuzzy affiliation function of the object of observation to each class with a set of values [0,1]. In the article shown representation of such function for quantitative characteristic in the form of a histogram. For qualitative attributes determined own values for each value. The new result of researches is a data structure for storing of the recognition process model, which allows to store together diverse characteristics and affiliation functions of different types at the same database tables. The proposed structure can be used in the process of the development of recognition systems software. It should be noted that will provide increased reliability of data storage by reducing the components of the database structure but also increased the complexity of the procedures and algorithms for saving and selecting the data.
References
Gorelik A. L., Skripkin V. A. Metody raspoznavanija [The Recognization Methods]. Moscow, Vysshaja Shkola Publ., 2004. 261 p.
Vjatchenin D. A. Nechetkie metody avtomaticheskoj klassifikacii [Indistinct Methods of Automatic Classification]. Мinsk, UP "Technoprint" Publ., 2004, 219 p.
Grachev V. M., Poprygin A. N. Metodika raspoznavanija klassov vozdushnyh ob#ektov v ASU PVO s ispol'zovaniem odnorodnoj funkcional'noj seti [Technique of air objects classes recognition in AirDefense ACS with use of uniform functional network]. Sb. nauchn. tr. KhVU [Collection of scientific papers of Kharkov Military University]. Kharkov, KhMU Publ., 1995, no. 8, pp. 49–54.
Vagis A., Gupal A. Jeffektivnost' bajesovskih procedur raspoznavanija [Efficiency of Bayesian procedures of recognition]. ITHEA International Scientific Socaety, 2008. Available at: http://www.foibg.com/ibs_isc/ibs-15/ibs-15-p11.pdf (accessed 15.09.2019).
Barskij A. B. Nejronnyeseti: raspoznavanie, upravlenie, prinjatiereshenij [Neural networks: recognition, management, decision-making]. Moscow, Finansyand Statistika Publ., 2004. 176 p.
Goloskokov A. Ye., Mel’nik K. V. Procedura diagnostuvannya stanu serdcevo-sudynnoyi systemy paciyentu na osnovi nechitkoyi logiky [The procedure of diagnosing the state of patient cardiovascular system based on fuzzy logic]. Visnyk NTU "KhPI" [Bulletin of the National Technical University "KhPI"]. Tematychnyy vypusk: Informatyka i modelyuvannya [Special issue: Informatics and modeling]. Kharkiv, NTU "KhPI" Publ., 2008, no. 49, pp. 101–104.
Pavlenko M. A. Metod formalizacii znanij o processe raspoznavanija situacij narushenija pravil dvizhenija vozdushnymi sudami [Method of knowledge formalization of process of recognition of the movement rules violation by aircrafts situations]. Systemy upravlinnya, navigaciyi i zvyazku [Control systems, navigation and communication]. Kyiv, GE "CSRI N&C" Publ., 2012, no. 2 (22), pp. 86–92.
Andrushko I. V. Rozpiznavannya peredavarijny’x ta avarijny’x sy’tuacij diagnostovany’x promy`slovy’x ob’yektiv na osnovi logiko-staty’sty’chny’x informacijny’x modelej [Recognition of pre-accident and emergency situations of diagnosed industrial objects on the basis of logical and statistical information models]. Shtuchny’j intelekt [Artificial Intelligence]. 2008, no. 4, pp. 309–316.
Singh V, Pongpaichet S, Jain R. Situation recognition from multimodal data. Proceedings of the 2016 ACM International Conference on Multimedia Retrieval (ICMR 2016). 2016, pp. 1–2.
Chetty G., Yamin M. A Novel Multimodal Data Analytic Scheme for Human Activity Recognition. Available at: https://link.springer.com/content/pdf/10.1007%2F978-3-642-55355-4_47.pdf (accessed 15.09.2019).
Dvukhglavov D. E., Muzyka O. V., Hlazkov S. O. Model of the situations recognition in conditions dissimilar and incomplete data. Visnyk NTU «KhPI»: zb. nauk. pr. Seriya: Sy’stemny’j analiz, upravlinnya ta informacijni texnologiyi. [Bulletin of NTU "KhPI". Series: System analysis, control and information technology]. Kharkiv, NTU "KhPI", 2016, no. 37 (1209), pp. 17–21.
Dovby’sh A. S. Osnovy’ proektuvannya intelektual’ny’x sy’stem. Sumy’, SumGU Publ., 2009, 171 p.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information TechnologiesAuthors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).