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Path Planning and Obstacle Avoidance of a Mobile Robot based on GWO Algorithm
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planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the performance of the proposed algorithm. Simulations results showed that the proposed path planning algorithm effective performance by finding the shortest and free-collision path in different collide environments. Furthermore, the superiority of the proposed algorithm was proved through comparisons with other famous path planning algorithms with different static environments.

 

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Creating Through Points in Linear Function with Parabolic Blends Path by Optimization Method
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The linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Multifactor Algorithm for Test Case Selection and Ordering
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Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Mon Aug 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Solid waste recycling and management cost optimization algorithm
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Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Common Fixed Point of a Finite-step Iteration Algorithm Under Total Asymptotically Quasi-nonexpansive Maps
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      Throughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.

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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
Sun Sep 01 2013
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The contractual budget: the ideal technique in planning and implementing capital budgeting projects: a strategy of preparing the contractual budget for Baghdad local government
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Public budget is the government's tool in achieving the objectives of economic and social development is the accounting curriculum to estimate state revenues and expenditures for years to come, as well as to have legal status as it is after the adoption of an official statement of government units to spend funds on items planned at the same time is a statement collect resources to finance these appropriations, if the primary objective of the budget initially limited to the achievement of financial and legislative control have evolved this function in the area of public administration turned attention from mere imposition of control over the money, which provides information to assist the Department to utilize available resources and prog

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Evaluation of routing protocol with multi-mobile sinks in WSNs using QoS and energy consumption parameters
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An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols i

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Publication Date
Tue Dec 30 2025
Journal Name
Alnahrain Journal Of Legal Scienci
Elements and Conditions of Personal Civil Liability (Based on Fault) for the Government for Damages Caused by Demonstrations: A Comparative Study
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This study examines the position of comparative legislation (French legislation, English legislation, and Egyptian legislation) in addressing the regulation of personal civil liability (based on fault) for the government. About the damages caused by demonstrations in terms of their legal nature, their legal basis, and the pillars and conditions of that responsibility. Then, we explain the position of the Iraqi legislator and compare it with what is the case in the legislation mentioned above

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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