A business intelligent technique for sentiment estimation by management sectors

2015 ◽  
Author(s):  
Sherine Rady
Keyword(s):  
Intelligent Technique

scholarly journals Application of Artificial Intelligence and Gamma Attenuation Techniques for Predicting Gas–Oil–Water Volume Fraction in Annular Regime of Three-Phase Flow Independent of Oil Pipeline’s Scale Layer

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1460
Author(s):  
Abdulaziz S. Alkabaa ◽  
Ehsan Nazemi ◽  
Osman Taylan ◽  
El Mostafa Kalmoun
Keyword(s):  
Gamma Radiation ◽  
Volume Fraction ◽  
Phase Flow ◽  
Gas Oil ◽  
Oil Pipeline ◽  
Intelligent Technique ◽  
Scale Layer ◽  
Three Phase ◽  
Three Phase Flow ◽  
Annular Regime

To the best knowledge of the authors, in former studies in the field of measuring volume fraction of gas, oil, and water components in a three-phase flow using gamma radiation technique, the existence of a scale layer has not been considered. The formed scale layer usually has a higher density in comparison to the fluid flow inside the oil pipeline, which can lead to high photon attenuation and, consequently, reduce the measuring precision of three-phase flow meter. The purpose of this study is to present an intelligent gamma radiation-based, nondestructive technique with the ability to measure volume fraction of gas, oil, and water components in the annular regime of a three-phase flow independent of the scale layer. Since, in this problem, there are several unknown parameters, such as gas, oil, and water components with different amounts and densities and scale layers with different thicknesses, it is not possible to measure the volume fraction using a conventional gamma radiation system. In this study, a system including a 241Am-133Ba dual energy source and two transmission detectors was used. The first detector was located diametrically in front of the source. For the second detector, at first, a sensitivity investigation was conducted in order to find the optimum position. The four extracted signals in both detectors (counts under photo peaks of both detectors) were used as inputs of neural network, and volume fractions of gas and oil components were utilized as the outputs. Using the proposed intelligent technique, volume fraction of each component was predicted independent of the barium sulfate scale layer, with a maximum MAE error of 3.66%.

Modelling and control of manipulators with flexible links working on land and underwater environments

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 461-470 ◽  
Author(s):  
Levent Gümüşel ◽  
Nurhan Gürsel Özmen
Keyword(s):  
Fuzzy Control ◽  
Control Method ◽  
Robot Manipulator ◽  
Control Methods ◽  
Control Laws ◽  
Linear Ordinary Differential Equations ◽  
Intelligent Technique ◽  
Wide Range ◽  
Classical Control ◽  
And Control

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

2018 ◽  
Vol 45 (5) ◽  
pp. 688-702 ◽  
Author(s):  
Dayal R. Parhi ◽  
Animesh Chhotray
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Weight Functions ◽  
Feasible Point ◽  
Content Type ◽  
Intelligent Technique ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Incremental Step

PurposeThis paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).Design/methodology/approachThis TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters.FindingsAuthenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%.Practical implicationsThis robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform.Originality/valueA new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

Advanced In-Process Control System for Sheet Stamping and Tube Hydroforming Processes

2014 ◽  
Vol 622-623 ◽  
pp. 3-14 ◽  
Author(s):  
Kenichi Manabe
Keyword(s):  
Process Control ◽  
Metal Forming ◽  
Tube Hydroforming ◽  
Essential Element ◽  
Forming Limit ◽  
Forming Process ◽  
Intelligent Technique ◽  
Sheet Stamping ◽  
Adaptive Process Control ◽  
Metal Forming Process

A sophisticated servo press with the digital control has been developed and attracted attention in recent years. By utilizing its high function in-process, servo presses have a potential to enhance the forming limit and to improve quality and accuracy of product not only in sheet stamping but also in tube hydroforming processes. On the other hand, in-process control and adaptive process control technologies in metal forming processes using intelligent technique and soft computing have been investigated and developed previously. Nowadays we are in a good environment to realize further advanced adaptive in-process control in metal forming process. To further advance this technology, sensing system is essential element and it should be applied to feedback control optimally in their forming operation. This paper describes the current situation on advanced intelligent process control technology for sheet stamping and tube hydroforming processes on the basis of the research results by the author.

Intelligent technique for human authentication using hand vein

2020 ◽  
Vol 5 (4) ◽  
pp. 263
Author(s):  
Mona A. Ahmed ◽  
Mohamed Roushdy ◽  
Abdel Badeeh M. Salem
Keyword(s):  
Intelligent Technique ◽  
Hand Vein

Intelligent Classification of Palm Oil Tree Pollination Using E-Nose

Mekatronika ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 28-37
Author(s):  
Abdul Rahim Jalil ◽  
Muhammad Sharfi Najib ◽  
Suhaimi Mohd Daud ◽  
Mujahid Mohamad
Keyword(s):  
Palm Oil ◽  
Case Based Reasoning ◽  
Artificial Intelligent ◽  
Male And Female ◽  
Intelligent Technique ◽  
Insect Activity ◽  
Artificial Intelligent Technique ◽  
Case Based ◽  
Odour Profile

The pollination period is one of the crucial steps needed to ensure crop yield increases, especially in palm oil palm plantations. Most of the research has difficulty determining the pollination period of palm oil. Many problems contribute to this problem, such as difficut to reach and depedency of the polination insect as the insect activity is influenced by the surrounding enviroment.E-Nose can help determine the period by classifiy odour pattern of the male and female palm oil flower. The pattern of each of the flowers were classified using cased – based reasoning artificial intelligent technique. This paper shows the research of the palm oil pollination flower odour profile pattern using case-based reasoning (CBR) classifier.

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