Expert-Statistical Processing of Data and the Method of Analogs in Solution of Applied Problems in Control Theory

Mandel, Alexander; Belyakov, Aleksei G.; Semenov, D.

doi:10.3182/20080706-5-kr-1001.00540

Cited by 5 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Adaptive algorithms for recalculation of estimated parameters of optimal two-level inventory control strategies for a restricted stock-out case are discussed in (Mandel, Belyakov, Semenov, 2008; ( ) …”

Section: Adaptive Algorithms For Evaluation Of "Myopic" Strategy Paramentioning

confidence: 99%

“…As shown in (Belyakov, Mandel, 2002a;Mandel, 2004;and Mandel, Belyakov, Semenov, 2008) interaction of the expert and the expert-statistical prediction system (ESPS) provides the set Z of analogs of the predictable object (PO) under consideration. For this set, the ESPS database contains information about "complete", that is, represented by much longer time series, realizations of operation of the analog objects.…”

Section: Expert-statistical Procedures Of Demand Prediction By the Anamentioning

confidence: 99%

“…The models and methods discussed are based on general methods of the adaptation theory (Tsypkin, 1968;Tsypkin, 1995) and expertstatistical approach in the form of the analog method (Belyakov, Mandel, 2002a;Belyakov, Mandel, 2002b;Mandel, 2004;Belyakov, Mandel, Semenov, 2008).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Models and Algorithms of Inventory Control in Case of Uncertainty

Mandel

2009

IFAC Proceedings Volumes

View full text Add to dashboard Cite

Section: Adaptive Algorithms For Evaluation Of "Myopic" Strategy Paramentioning

confidence: 99%

Section: Expert-statistical Procedures Of Demand Prediction By the Anamentioning

confidence: 99%

See 1 more Smart Citation

Models and Algorithms of Inventory Control in Case of Uncertainty

Mandel

2009

IFAC Proceedings Volumes

View full text Add to dashboard Cite

“…It is necessary to understand exactly how the received signal is close to the real one, that is, it is always necessary to evaluate the final result containing a certain value of the hidden error. Now, a large number of solutions have been proposed that form the fundamental basis for selection of some efficient methods for processing the measured data [1][2][3][4][5][6][7][8][9][10]. In cases, when the analyzed data source is easily fitted to well-known analytical dependencies that follow from probability theory or from some proposed model, the calibration sensor problems do not arise usually.…”

Section: Introduction and Formulation Of The Problemmentioning

confidence: 99%

“…In analysis of various types of data, a potential researcher makes some assumption about the correspondence (even remote and unjustified) of the studied dataset to a certain distribution law. Hypotheses are tested using various known criteria [1][2][3][4][5]. For example, the F-distribution is the ratio of two independent quantities, scaled relative to the original data.…”

Section: Introduction and Formulation Of The Problemmentioning

confidence: 99%

Application of the Complex Moments for Selection of an Optimal Sensor

Nigmatullin

Alexandrov

2021

Sensors

View full text Add to dashboard Cite

In the first time we apply the statistics of the complex moments for selection of an optimal pressure sensor (from the available set of sensors) based on their statistical/correlation characteristics. The complex moments contain additional source of information and, therefore, they can realize the comparison of random sequences registered for almost identical devices or gadgets. The proposed general algorithm allows to calculate 12 key correlation parameters in the significance space. These correlation parameters allow to realize the desired comparison. New algorithm is rather general and can be applied for a set of other data if they are presented in the form of rectangle matrices. Each matrix contains N data points and M columns that are connected with repetitious cycle of measurements. In addition, we want to underline that the value of correlations evaluated with the help of Pearson correlation coefficient (PCC) has a relative character. One can introduce also external correlations based on the statistics of the fractional/complex moments that form a complete picture of correlations. To the PCC value of internal correlations one can add at least 7 additional external correlators evaluated in the space of fractional and complex moments in order to realize the justified choice. We do suppose that the proposed algorithm (containing an additional source of information in the complex space) can find a wide application in treatment of different data, where it is necessary to select the “best sensors/chips” based on their measured data, presented usually in the form of random rectangle matrices.

show abstract

Expert-Statistical Data Processing Using the Method of Analogs

Mandel

2017

2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT)

View full text Add to dashboard Cite

Expert-Statistical Processing of Data and the Method of Analogs in Solution of Applied Problems in Control Theory

Cited by 5 publications

References 3 publications

Models and Algorithms of Inventory Control in Case of Uncertainty

Models and Algorithms of Inventory Control in Case of Uncertainty

Application of the Complex Moments for Selection of an Optimal Sensor

Expert-Statistical Data Processing Using the Method of Analogs

Contact Info

Product

Resources

About