Privacy boundary determination of smart meter data using an artificial intelligence adversary

2021 ◽  
Author(s):  
Xiao‐Yu Zhang ◽  
Chris Watkins ◽  
Clive Cheong Took ◽  
Stefanie Kuenzel
Keyword(s):  
Artificial Intelligence ◽  
Smart Meter ◽  
Boundary Determination

scholarly journals Interaction Boundary Determination of Renewable Energy Sources to Estimate System Strength Using the Power Flow Tracing Strategy

2021 ◽  
Vol 13 (3) ◽  
pp. 1569
Author(s):  
Namki Choi ◽  
Byongjun Lee ◽  
Dohyuk Kim ◽  
Suchul Nam
Keyword(s):  
Renewable Energy ◽  
Power Flow ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Test Results ◽  
Boundary Determination ◽  
Actual Interaction ◽  
Power Flow Tracing ◽  
Estimate System

System strength is an important concept in the integration of renewable energy sources (RESs). However, evaluating system strength is becoming more ambiguous due to the interaction of RESs. This paper proposes a novel scheme to define the actual interaction boundaries of RESs using the power flow tracing strategy. Based on the proposed method, the interaction boundaries of RESs were identified at the southwest side of Korea Electric Power Corporation (KEPCO) systems. The test results show that the proposed approach always provides the identical interaction boundaries of RESs in KEPCO systems, compared to the Electric Reliability Council of Texas (ERCOT) method. The consistent boundaries could be a guideline for power-system planners to assess more accurate system strength, considering the actual interactions of the RESs.

Determination of body fat percentage by electrocardiography signal with gender based artificial intelligence

2021 ◽  
Vol 68 ◽  
pp. 102650
Author(s):  
Muhammed Kürşad Uçar ◽  
Zeliha Uçar ◽  
Kübra Uçar ◽  
Mehmet Akman ◽  
Mehmet Recep Bozkurt
Keyword(s):  
Artificial Intelligence ◽  
Body Fat ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Gender Based

Path Following System for Cooperative Mobile Robots

2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu
Keyword(s):  
Artificial Intelligence ◽  
Mobile Robots ◽  
Path Following ◽  
Path Generation ◽  
Cooperative Robots ◽  
Generation System ◽  
Robot Systems ◽  
Simulation Results ◽  
Trajectory Generator

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.

The Ship Domain – A Criterion of Navigational Safety Assessment in an Open Sea Area

2008 ◽  
Vol 62 (1) ◽  
pp. 93-108 ◽  
Author(s):  
Zbigniew Pietrzykowski ◽  
Janusz Uriasz
Keyword(s):  
Artificial Intelligence ◽  
Safety Assessment ◽  
Research Results ◽  
Safe Navigation ◽  
Number Of Factors ◽  
Open Sea ◽  
Sea Area ◽  
Point Of Departure ◽  
Shape And Size

One of the basic tasks in shipping is to ensure safe navigation of vessels. The concept of the ship domain is of major importance in the assessment of a navigational situation and the avoidance of ship collisions. It is difficult to determine a ship domain as its shape and size depend on a number of factors. One question to be answered before the determination of the ship domain is which method to use: statistical, analytic, or expert method using artificial intelligence tools; other questions are connected with domain interpretation. The authors have analyzed the ship domain as a criterion for the assessment of ship navigational safety in an encounter situation in the open sea. The research results are used to answer some of the questions.Part 2 includes definitions of the ship domain and ship fuzzy domain. Part 3, in turn, presents methods of their determination as well as relevant questions. The results of the authors' research, described in Part 4, make up a basis for the determination of the domain and ship fuzzy domain. These have been determined with the so-called dynamic domains as a point of departure. The criteria of ship domain and closest point of approach are compared and discussed. Encounters of various size ships are considered in Part 5. The research and its results are described. Both ship domains and ship fuzzy domains of encountering ships are analyzed. Then, conclusions have been formulated in relation to the effect of the sizes of encountering ships on the shapes and sizes of their domains. Final conclusions are given in Part 6.

scholarly journals Stochastic Fuzzy Algorithms for Impairment of Assets Management

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Marcel Ioan Bolos ◽  
Victoria Bogdan ◽  
Ioana Alexandra Bradea ◽  
Claudia Diana Sabau Popa ◽  
Dorina Nicoleta Popa
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Fuzzy Numbers ◽  
Cash Flows ◽  
The Other ◽  
Dual Purpose ◽  
Fuzzy Algorithms ◽  
Tangible Assets ◽  
The Impact

The present paper aims to analyze the impairment of tangible assets with the help of artificial intelligence. Stochastic fuzzy numbers have been introduced with a dual purpose: on one hand to estimate the cash flows generated by tangible assets exploitation and, on the other hand, to ensure the value ranges stratifications that define these cash flows. Estimation of cash flows using stochastic fuzzy numbers was based on cash flows generated by tangible assets in previous periods of operation. Also, based on the Lagrange multipliers, were introduced: the objective function of minimizing the standard deviations from the recorded value of the cash flows generated by the tangible assets, as well as the constraints caused by the impairment of tangible assets identification according to which the cash flows values must be equal to the annual value of the invested capital. Within the determination of the impairment value and stratification of the value ranges determined by the cash flows using stochastic fuzzy numbers, the impairment of assets risk was identified. Information provided by impairment of assets but also the impairment risks, is the basis of the decision-making measures taken to mitigate the impact of accumulated impairment losses on company’s financial performance.

scholarly journals Performance Comparison of Artificial Intelligence Techniques for Non-intrusive Electrical Load Monitoring

2018 ◽  
Vol 7 (2) ◽  
pp. 143-152
Author(s):  
Khairuddin Khalid ◽  
Azah Mohamed ◽  
Ramizi Mohamed ◽  
Hussain Shareef
Keyword(s):  
Artificial Intelligence ◽  
Reactive Power ◽  
Performance Comparison ◽  
Support Vector ◽  
Fluorescent Light ◽  
Time Interval ◽  
Smart Meter ◽  
Air Conditioner ◽  
Artificial Intelligence Techniques ◽  
Load Monitoring

The increased awareness in reducing energy consumption and encouraging response from the use of smart meters have triggered the idea of non-intrusive load monitoring (NILM). The purpose of NILM is to obtain useful information about the usage of electrical appliances usually measured at the main entrance of electricity to obtain aggregate power signal by using a smart meter. The load operating states based on the on/off loads can be detected by analysing the aggregate power signals. This paper presents a comparative study for evaluating the performance of artificial intelligence techniques in classifying the type and operating states of three load types that are usually available in commercial buildings, such as fluorescent light, air-conditioner and personal computer. In this NILM study, experiments were carried out to collect information of the load usage pattern by using a commercial smart meter. From the power parameters captured by the smart meter, effective signal analysis has been done using the time time (TT)-transform to achieve accurate load disaggregation. Load feature selection is also considered by using three power parameters which are real power, reactive power and the TT-transform parameters. These three parameters are used as inputs for training the artificial intelligence techniques in classifying the type and operating states of the loads. The load classification results showed that the proposed extreme learning machine (ELM) technique has successfully achieved high accuracy and fast learning compared with artificial neural network and support vector machine. Based on validation results, ELM achieved the highest load classification with 100% accuracy for data sampled at 1 minute time interval.

scholarly journals STATE CADASTRAL ASSESSMENT OF REAL ESTATE AND NATURAL RESOURCES IN THE DIGITAL ECONOMY OF RUSSIA (DEFINITION OF ECONOMIC STANDARDS FOR THE RATIONAL USE OF REAL ESTATE PROPERTIES AND NATURAL RESOURCES)

2021 ◽  
Vol 3 (1) ◽  
pp. 269-276
Author(s):  
Alexander D. Vlasov
Keyword(s):  
Artificial Intelligence ◽  
Real Estate ◽  
Natural Resources ◽  
Digital Economy ◽  
Rational Use ◽  
Definition Of ◽  
Organizational Problems

Methodological and organizational problems of accounting, appraisal of real estate objects and natural resources of Russia are posed. The technology of accounting and determination of economic standards for the rational use of real estate and natural resources in the digital economy of Russia based on artificial intelligence is proposed.

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