The Control Automation System Method Based on Combined Implementation of Fuzzy Logic and Discrete Automation Systems

Dintsis, Danil; Симанков, Владимир Сергеевич

doi:10.1109/ems.2013.15

Cited by 2 publications

(7 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Allocate a set of described attributes of essences. Based on it create a set T of fuzzy model attributes as mentioned in [2,3].…”

Section: Fuzzy Model Synthesis Algorithm Based On a Preceding Lingualmentioning

confidence: 99%

“…We consider a method of compliance between model and object based on research of mutual consistency of elements. The method is based on a ∪-operation, and indicates subsets, which can describe an object behavior if used in common [2,3]: …”

Section: Scope Definition For Fuzzy Sets Usage In Control and Simulatmentioning

confidence: 99%

“…Let us mark sets of keywords, and consider them as fuzzy model objects. At the first step, we may consider all nouns as fuzzy model objects [1][2][3].…”

Section: Fuzzy Model Synthesis Based On Lingual Model Analysis For Tementioning

confidence: 99%

“…Creating an analytical model as the first step of the system synthesis is based on intrinsic and semantic analysis of input data. Establishment of collaboration between specialists in different knowledge areas (technology, information, business, or others) is usually one of the main problems and challenges almost in all practice-based projects [3]. Factor analysis or lingual models may provide partial decision of the problem.…”

Section: Extension For Fuzzy Model Definition Area 21 Introductionmentioning

confidence: 99%

“…Let us consider the control system for an informational object as a "black box" with two sets of inputs and outputs [3]. Two main inputs are a math (or analytical) model, and data.…”

Section: Extension For Fuzzy Model Definition Area 21 Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Implementing Complex Fuzzy Analysis for Business Planning Systems

Dintsis¹

2017

Modern Fuzzy Control Systems and Its Applications

Self Cite

View full text Add to dashboard Cite

show abstract

“…Allocate a set of described attributes of essences. Based on it create a set T of fuzzy model attributes as mentioned in [2,3].…”

Section: Fuzzy Model Synthesis Algorithm Based On a Preceding Lingualmentioning

confidence: 99%

Section: Scope Definition For Fuzzy Sets Usage In Control and Simulatmentioning

confidence: 99%

“…Let us mark sets of keywords, and consider them as fuzzy model objects. At the first step, we may consider all nouns as fuzzy model objects [1][2][3].…”

Section: Fuzzy Model Synthesis Based On Lingual Model Analysis For Tementioning

confidence: 99%

Section: Extension For Fuzzy Model Definition Area 21 Introductionmentioning

confidence: 99%

“…Let us consider the control system for an informational object as a "black box" with two sets of inputs and outputs [3]. Two main inputs are a math (or analytical) model, and data.…”

Section: Extension For Fuzzy Model Definition Area 21 Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Implementing Complex Fuzzy Analysis for Business Planning Systems

Dintsis¹

2017

Modern Fuzzy Control Systems and Its Applications

Self Cite

View full text Add to dashboard Cite

show abstract

A Smart Home Architecture for Smart Energy Consumption in a Residence With Multiple Users

et al. 2021

View full text Add to dashboard Cite

Smart Energy Control Systems (SECS) has been increasingly implemented in the Smart homes scenario, due to the possibility of conditioning and controlling residential energy consumption, thus contributing to reducing energy losses and unnecessary electrical consumption. With the evolution of embedded systems in conjunction with the Internet of Things (IoT), Smart Outlet (SO), and devices that promote the Users Indoor Identification (UII) environments, they have assumed fundamental roles in the acquisition of data from electrical devices and also in the mapping of the individualized consumption of each resident throughout the day, providing essential information for SECS Systems as a way to assist in energy balance with minimal impact on the daily usability of electrical equipment. However, in most of the works that propose these types of assistance to SECS based on SO and UII, they have a massive implementation of sensors throughout the residence, misinterpretation of the data generated by the residents, difficulty in the identification of multiple residents. Thus, the present work proposes an evolution of an SECS architecture called SmartCom, with the implementation of accurate identification of electrical equipment through Near Field Communication (NFC)-based SO (data transfer between the appliance and the SO) and of multiple inhabitants through Wi-Fi handover using smartphones, with the least possible impact on the user's comfort, as well as in the building structure, achieving a rebalanced residential energy consumption 87.3% of the time it was used.

show abstract

The Control Automation System Method Based on Combined Implementation of Fuzzy Logic and Discrete Automation Systems

Cited by 2 publications

References 1 publication

Implementing Complex Fuzzy Analysis for Business Planning Systems

Implementing Complex Fuzzy Analysis for Business Planning Systems

A Smart Home Architecture for Smart Energy Consumption in a Residence With Multiple Users

Contact Info

Product

Resources

About