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An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Aquatic Sience
Helminths and their fish hosts as bioindicators of heavy metal pollution: A review
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
SBOA: A Novel Heuristic Optimization Algorithm
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A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

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Publication Date
Thu Aug 01 2019
Journal Name
مجلة العلوم الاقتصادية والإدارية
Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
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Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

Publication Date
Sat May 31 2025
Journal Name
3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges
Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies
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Publication Date
Tue Nov 01 2016
Journal Name
2016 International Conference On Advanced Mechatronic Systems (icamechs)
Hierarchical sliding mode control applied to a single-link flexible joint robot manipulator
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Trajectory tracking and vibration suppression are essential objectives in a flexible joint manipulator control. The flexible joint manipulator is an under-actuated system, in which the number of control actions is less than the degree of freedom to be controlled. It is very challenging to control the underactuated nonlinear system with two degree of freedom. This paper presents a hierarchical sliding mode control (HSMC) for a rotary flexible joint manipulator (RFJM). Firstly, the rotary flexible joint manipulator is modeled by two subsystems. Secondly, the sliding surfaces for both subsystems are constructed. Finally, the control action is designed based on the Lyapunov function. Computer simulation results demonstrate the effectiveness of

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI
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“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

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