Forensic Block Chain and it's linkage with Artificial Intelligence: A new Approach

2021 ◽  
Author(s):  
Nikitha Mani ◽  
Soham Sanjay Parab ◽  
Srikuja Manaswini ◽  
Sharon Philip ◽  
Parli B Hari ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
New Approach ◽  
Block Chain

scholarly journals New approach to evaluate the equivalent circulating density (ECD) using artificial intelligence techniques

2018 ◽  
Vol 9 (2) ◽  
pp. 1569-1578 ◽  
Author(s):  
Khaled Z. Abdelgawad ◽  
Mahmoud Elzenary ◽  
Salaheldin Elkatatny ◽  
Mohamed Mahmoud ◽  
Abdulazeez Abdulraheem ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
New Approach ◽  
Artificial Intelligence Techniques

scholarly journals Artificial Intelligence, Smart Contract and Islamic Finance

2018 ◽  
Vol 14 (2) ◽  
pp. 145 ◽  
Author(s):  
Siti Rohaya Mat Rahim ◽  
Zam Zuriyati Mohamad ◽  
Juliana Abu Bakar ◽  
Farhana Hanim Mohsin ◽  
Norhayati Md Isa
Keyword(s):  
Artificial Intelligence ◽  
Computer Code ◽  
Islamic Finance ◽  
Human Intelligence ◽  
Human Beings ◽  
Finance Industry ◽  
Smart Contract ◽  
Huge Impact ◽  
Block Chain

This study examines the two important aspect of latest technology issues in Islamic finance that related to artificial intelligence (AI) and smart contract. AI refers to the ability of machines to understand, think, and learn in a similar way to human beings, indicating the possibility of using computers to simulate human intelligence. Smart contract is a computer code running on top of a block-chain containing a set of rules under which the parties to that smart contract agree to interact with each other. The main objectives of this article are to evaluate the operations of AI and smart contract, to make comparison between the operations of AI and smart contract. This article concludes that AI and smart contract will have a huge impact in future for Islamic Finance industry.

Artificial Intelligence Based on Biological Neurons

2020 ◽  
pp. 25-53
Author(s):  
Rinat Galiautdinov
Keyword(s):  
Artificial Intelligence ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Next Generation ◽  
New Approach ◽  
Home Based

The chapter describes the new approach in artificial intelligence based on simulated biological neurons and creation of the neural circuits for the sphere of IoT which represent the next generation of artificial intelligence and IoT. Unlike existing technical devices for implementing a neuron based on classical nodes oriented to binary processing, the proposed path is based on simulation of biological neurons, creation of biologically close neural circuits where every device will implement the function of either a sensor or a “muscle” in the frame of the home-based live AI and IoT. The research demonstrates the developed nervous circuit constructor and its usage in building of the AI (neural circuit) for IoT.

An Artificial Intelligence Based Approach for High Impedance Faults Analysis in Distribution Networks

2012 ◽  
Vol 1 (2) ◽  
pp. 44-59 ◽  
Author(s):  
M. S. Abdel Aziz ◽  
M. A. Moustafa Hassan ◽  
E. A. El-Zahab
Keyword(s):  
Artificial Intelligence ◽  
Distribution System ◽  
Fault Location ◽  
Fuzzy Inference ◽  
Distribution Networks ◽  
Inference System ◽  
New Approach ◽  
High Impedance ◽  
Neuro Fuzzy ◽  
High Impedance Faults

This paper presents a new approach for high impedance faults analysis (detection, classification and location) in distribution networks using Adaptive Neuro Fuzzy Inference System. The proposed scheme was trained by data from simulation of a distribution system under various faults conditions and tested for different system conditions. Details of the design process and the results of performance using the proposed method are discussed. The results show the proposed technique effectiveness in detecting, classifying, and locating high impedance faults. The 3rd harmonics, magnitude and angle, for the 3 phase currents give superior results for fault detection as well as for fault location in High Impedance faults. The fundamental components magnitude and angle for the 3 phase currents give superior results for classification phase of High Impedance faults over other types of data inputs.

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