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A Novel Invasive Weed Optimization Algorithm (IWO) by Whale Optimization Algorithm(WOA) to solve Large Scale Optimization Problems
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Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invasive Weed Optimization Algorithm (IWO), as for the Whale Optimization Algorithm (WOA) uses the intelligence of the swarms to reach the goal and achieve the best solution, which simulates the unique hunting behavior of humpback whales, which is called fishing by bubble trap hunting by creating distinctive bubbles along a circle or a path in the form of 9 has appeared for the first time in 2016 by Mirjalili and Lewis. In order to benefit from the intelligence of the flocks and to avoid falling into local solutions, the new hybridization between the IWO and WOA algorithm was proposed to launch the new hybrid algorithm (IWOWOA). The new hybrid algorithm (IWOWOA) was applied on 23 functions of large scale optimization problems, The proposed algorithm showed very high efficiency in solving these functions. The proposed algorithm was able to reach the optimal solutions by achieving the minimum value of most of these functions. This algorithm was compared with the basic algorithms IWO, WOA and two algorithms that follow the swarm system these algorithms are particle swarm optimization (PSO) and chicken swarm optimization (CSO) [7], they have been statistically tested by calculating the mean arithmetic μ and standard deviation σ for these functions.

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Publication Date
Thu Jan 01 2009
Journal Name
2009 Wri International Conference On Communications And Mobile Computing
Optimization of Cooperation Sensing Spectrum Performance
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Cooperation spectrum sensing in cognitive radio networks has an analogy to a distributed decision in wireless sensor networks, where each sensor make local decision and those decision result are reported to a fusion center to give the final decision according to some fusion rules. In this paper the performance of cooperative spectrum sensing examines using new optimization strategy to find optimal weight and threshold curves that enables each secondary user senses the spectrum environment independently according to a floating threshold with respect to his local environment. Our proposed approach depends on proving the convexity of the famous optimization problem in cooperative spectrum sensing that stated maximizing the probability of detec

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Publication Date
Fri Apr 20 2018
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Optimization of Digital Histopathology Image Quality
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One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method
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Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drilling Optimization by Using Advanced Drilling Techniques in Buzurgan Oil Field
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Efficient and cost-effective drilling of directional wells necessitates the implementation of best drilling practices and advanced techniques to optimize drilling operations. Failure to adequately consider drilling risks can result in inefficient drilling operations and non-productive time (NPT). Although advanced drilling techniques may be expensive, they offer promising technical solutions for mitigating drilling risks. This paper aims to demonstrate the effectiveness of advanced drilling techniques in mitigating risks and improving drilling operations when compared to conventional drilling techniques. Specifically, the advanced drilling techniques employed in Buzurgan Oil Field, including vertical drilling with mud motor, managed pres

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Publication Date
Wed Aug 21 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Optimization of a Surface-Mounted Permanent-Magnet Linear Synchronous Motor with Maxwell ANSYS
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Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Classical and Statistical Optimization of Medium Composition for Promoting Prodigiosin Produced by Local Isolate of Serratia Marcescens
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Prodigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Engineering
Optimal Economic Design of Diversion Structures during Construction of a Dam by Particle Swarm Optimization
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Science And Research (ijsr)
Optimal Economic Design of Diversion Structures during Construction of a Dam by Particle Swarm Optimization
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Diverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Electron lens Optimization for Beam Physics Research using the Integrated Optics Test Accelerator
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This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain  control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values ​​and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.

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