Determination of material deformation rate based on artificial intelligence using surface microstructure images

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.

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

Journal of Navigation ◽

10.1017/s0373463308005018 ◽

2008 ◽

Vol 62 (1) ◽

pp. 93-108 ◽

Cited By ~ 96

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.

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Stochastic Fuzzy Algorithms for Impairment of Assets Management

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2020.1.3690 ◽

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.

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A Comparative Analysis of Determination of Design Parameters of Boost and Buck–Boost Converters Using Artificial Intelligence

Advances in Systems, Control and Automation - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-10-4762-6_11 ◽

2017 ◽

pp. 117-125

Author(s):

Ipsita Das ◽

Moumi Pandit

Keyword(s):

Artificial Intelligence ◽

Comparative Analysis ◽

Design Parameters ◽

Boost Converters

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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)

Interexpo GEO-Siberia ◽

10.33764/2618-981x-2021-3-1-269-276 ◽

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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Digital Economy and Anti-Corruption: New Digital Models

SHS Web of Conferences ◽

10.1051/shsconf/20197103004 ◽

2019 ◽

Vol 71 ◽

pp. 03004

Author(s):

E.L. Sidorenko ◽

A.A. Lykov

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Internet Of Things ◽

Crime Prevention ◽

Digital Technologies ◽

Digital Economy ◽

Digital Models ◽

Research Results ◽

Corruption Prevention

The authors of this paper consider promising areas of the corruption prevention using the latest digital technologies: Blockchain, Internet of Things, Artificial Intelligence and Big Data. The purpose of this research is the analysis of advantages of the digital economy development in terms of solving social problems and crime prevention. The authors also show functional digital models of the anti-corruption compliance are defined. In addition, the research results include the determination of some shortcomings of the proposed models associated with the imperfection of the current legislation.

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Smart Education with artificial intelligence based determination of learning styles

Procedia Computer Science ◽

10.1016/j.procs.2018.05.095 ◽

2018 ◽

Vol 132 ◽

pp. 834-842 ◽

Cited By ~ 27

Author(s):

Richa Bajaj ◽

Vidushi Sharma

Keyword(s):

Artificial Intelligence ◽

Learning Styles ◽

Smart Education

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Prior Determination of Flash Floods: Artificial Intelligence Based Predictive Analysis Using Modified Cuckoo Search

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.8755 ◽

2020 ◽

Vol 17 (2) ◽

pp. 990-995

Author(s):

Talha Ahmed Khan ◽

Muhammad Alam ◽

Kushsairy Kadir ◽

Zeeshan Shahid ◽

M. S. Mazliham

Keyword(s):

Artificial Intelligence ◽

Water Pressure ◽

Cuckoo Search ◽

Flash Floods ◽

Rapid Identification ◽

Predictive Analysis ◽

Direct Observations ◽

The Pacific ◽

The Pacific Ocean

Flash floods are considered as the most intense hazard therefore rapid identification is needed. Tsunami also causes flash floods as it is commonly generated around the Pacific Ocean. Flash floods are also caused by the severely blocked streams in heavy rainfall. Floods have ended up so many lives more than the other natural hazards and also devastated precious belongings and infrastructures. Cattles have also been affected by the floods event. Floods devastate the construction and infrastructure like roads, bridges and buildings that comes in the vicinity of effected area by flood. Breakdown and overflow of dams may produce the deadly flash floods to the populated area and environs. Many strategies and methods have been followed to determine the flash floods on early basis so that evacuation announcements may be propagated. Numerous researches have been studied and carried out to accomplish this task. Development of dams and reservoirs have been given more significance. Artificial Intelligence based competent decision-making algorithms like Bayesian classifier, PSO, ANN, NNARX, SVM and GA have been applied to achieve more accuracy in predictive analysis. Direct observations from the sensors and data from the meteorological department have also been used for the predictive analysis of flash floods. Many yardstick parameters have been proposed in past researches to identify the flash floods vigorously like environmental CO2 levels, precipitation velocity, wind speed, upstream level, height of the water, pressure, temperature and cloud to ground flashes. In this research papers a novel Artificial Intelligence based approach Modified Cuckoo Search (MCS) has been adopted to forecast the flash floods more rapidly and accurately. Obtained results in the MATLAB have proved that Modified cuckoo search with the combination of Artificial Neural Network worked better than the recent available methods. Results have also been validated by comparing the MLP-PSO.

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