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Article
An Improved Technique Based on Firefly Algorithm to Estimate the Parameters of the Photovoltaic Model

Author: Issa Ahmed Abed
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2016 Volume: 12 Issue: 2 Pages: 137-145
Publisher: Basrah University جامعة البصرة

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Abstract

This paper present a method to enhance the firefly algorithm by coupling with a local search. The constructed technique is applied to identify the solar parameters model where the method has been proved its ability to obtain the photovoltaic parameters model. Standard firefly algorithm (FA), electromagnetism-like (EM) algorithm, and electromagnetism-like without local (EMW) search algorithm all are compared with the suggested method to test its capability to solve this model.


Article
Design a Fuzzy PID Controller for Trajectory Tracking of Mobile Robot

Authors: M.J. Mohamed --- M.Y. Abbas
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 1 Part (A) Engineering Pages: 100-110
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

In this paper, a trajectory tracking control for a non-holonomic differential wheeled mobile robot (WMR) system is presented. A big number of investigations have been used the kinematic model of mobile robot which is a nonlinear model in nature, thus a hard task to control it. This work focuses on the design of fuzzy PID controller tuned with a firefly optimization algorithm for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller's parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with the least possible value of error. Matlab Simulation results show that a good performance and robustness of the controller. This is confirmed by the value of minimized tracking error and the smooth velocity especially concerning presence of external disturbance or change in initial position of mobile robot.


Article
Design of keystream Generator utilizing Firefly Algorithm

Authors: Mohammed Salih Mahdi --- Nidaa Flaih Hassan
Journal: Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات ISSN: 20740204 / 25213504 Year: 2018 Volume: 10 Issue: 3 Pages: Comp Page 91-99
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

Stream cipher is one of encryption procedures for sending data in internet; stream cipher is suitable in telecommunications and real-time apps. The robustness measurement of stream cipher is according to the randomness of keystream that is utilized. If the random series of keystream generator is low, the keystream of stream cipher can be read and encrypted data by stream cipher become vulnerable to attackers. This paper utilizes Firefly Algorithm based Local Key Generation for generation keystream. The generated keystream is independent of original messages. The randomness of keystream series of Firefly passing the five standard criteria. The suggested keystream generator is wordestablished appropriated to fast real-time apps than are bit-established linear stream ciphers. Furthermore, the suggested keystream generator satisfies the three demands of benchmarks such as maximum correlation, robust randomness and huge complexity.


Article
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
تصميم وحدة سيطرة حركية عصبية لتتبع مسار الروبوتات المتنقلة بعجلات على أساس المحسن الهجين بين خوارزمية اليرعات المضيئة وخوارزمية خلية النحل

Authors: Nizar Hadi Abbas نزار هادي عباس --- Basma Jumia saleh بسمة جمعة صالح
Journal: Al-Khwarizmi Engineering Journal مجلة الخوارزمي الهندسية ISSN: 18181171 23120789 Year: 2016 Volume: 12 Issue: 1 Pages: 45-60
Publisher: Baghdad University جامعة بغداد

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Abstract

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 implemented based on hybrid Crossoved Firefly Algorithm with Artificial Bee Colony (CFA-ABC) to tune the controller's parameters to achieve the optimal path. The performance of the hybrid optimization algorithm is verified by various benchmark functions. The simulation results show that the utilizing of CFA and (CFA-ABC ) are better than the original Firefly Algorithm. A simulation example is given to indicate the effectiveness of the proposed algorithm, the results have been done using MATLAB (R2013b), and all trajectory tracking results with two reference trajectories (circular and lemniscates ) are presented.

يقدم هذا البحث , تصميما مسيطرا لتتبع مسار عجلة الانسان الالي المتحرك المبني على أساس مسيطر تكاملي حركي عصبي لتوجيه الروبوت المحمول المصنع من قبل شركة National Instrument , الغاية من المسيطر هي تقريب السرعة الحقيقية للأنسان الالي اقرب ما يكون من السرعة المطلوبة بجعل مقدار معدل الخطا اقرب الى الصفر. المسيطر المقترح في هذا البحث يتكون من طبقتين: الطبقة الأولى هي نظام شبكة عصبية متعدد الطبقات لتتبع المسار المطلوب و الطبقة الثانية هي طبقة الخوارزمية الأمثلية والتي تشمل خوارزمية هجينة محسنة وهي مكونة من خوارزمية اليرعات المضيئة وخوارزمية خلية النحل وتستخدم لأيجاد أفضل قيم للمسيطر والوصول للمسار الامثل. من خلال نتائج المحاكاة, اثبت المسيطر المقترح وخوارزمية الامثلية كفاءتهما بالوصول الى مقدار خطا وبأقل قيمة وتمت المحاكاة بأستخدام برنامج الماتلاب وتم تطبيقها على نوعين من المسارات (الدائري والانفنتي).


Article
Reactive Power Optimization with Chaotic Firefly Algorithm and Particle Swarm Optimization in A Distribution Subsystem Network

Authors: Hamza Yapıcı --- Nurettin Çetinkaya
Journal: Iraqi Journal for Electrical And Electronic Engineering المجلة العراقية للهندسة الكهربائية والالكترونية ISSN: 18145892 Year: 2016 Volume: 12 Issue: 1 Pages: 71-78
Publisher: Basrah University جامعة البصرة

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Abstract

In this paper the minimization of power losses in a real distribution network have been described by solving reactivepower optimization problem. The optimization has been performed and tested on Konya Eregli Distribution Network in Turkey,a section of Turkish electric distribution network managed by MEDAŞ (Meram Electricity Distribution Corporation). Thenetwork contains about 9 feeders, 1323 buses (including 0.4 kV, 15.8 kV and 31.5 kV buses) and 1311 transformers. This paperprefers a new Chaotic Firefly Algorithm (CFA) and Particle Swarm Optimization (PSO) for the power loss minimization in areal distribution network. The reactive power optimization problem is concluded with minimum active power losses by theoptimal value of reactive power. The formulation contains detailed constraints including voltage limits and capacitor boundary.The simulation has been carried out with real data and results have been compared with Simulated Annealing (SA), standardGenetic Algorithm (SGA) and standard Firefly Algorithm (FA). The proposed method has been found the better results thanthe other algorithms.


Article
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
تطوير موازنة الاحمال لأنترنت الأشياء - الحوسبة السحابية اعتمادا على خوارزميات اليراعة المتقدمة والدورية المرجحة

Authors: Marwa M. Abed مروة محمد عبد --- Manal F. Younis منال فاضل يونس
Journal: Baghdad Science Journal مجلة بغداد للعلوم ISSN: 20788665 24117986 Year: 2019 Volume: 16 Issue: 1 Pages: 130-139
Publisher: Baghdad University جامعة بغداد

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Abstract

The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities. Cloud computing can be used to store big data. The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual resource, by combining two types of algorithms: dynamic algorithm (adaptive firefly) and static algorithm (weighted round robin). The results show improvement in resource utilization, increased productivity, and reduced response time.

أدى التطور في إنترنت الأشياء (IoT) إلى ربط البلايين من الأجهزة المادية غير المتجانسة معاً لتحسين نوعية الحياة البشرية، من خلال جمع البيانات من بيئتهم. يجب تخزين هذه البيانات الهائلة التي تم تجميعها في سعة تخزين كبيرة بالإضافة إلى قدرات حاسوبية عالية، التي توفيرها الحوسبة السحابية. يتم نقل بيانات أجهزة IoT باستخدام نوعين من البروتوكولات. نقل الرسائل في قائمة انتظار النقل (MQTT) وHypertext Transfer Protocol (HTTP). يهدف هذا البحث لتحسين أداء النظام وزيادة الموثوقية من خلال الاستخدام الفعال للموارد. من خلال، استخدام موازنة التحميل في الحوسبة السحابية لتوزيع عبء العمل ديناميكيًا عبر العقد لتجنب زيادة التحميل على أي مورد فردي. من خلال الجمع بين نوعين من الخوارزميات: الديناميكية خوارزمية (اليراعة المتقدمة (Advanced Firefly Algorithm والخوارزمية الثابتة (Weighted Round Robin Algorithm). وأظهرت النتيجة تحسن في استخدام الموارد وزيادة الإنتاجية وتقليل وقت وقت الاستجابة.


Article
Design Interval Type-2 Fuzzy Like (PID) Controller for Trajectory Tracking of Mobile Robot

Authors: Mustafa Y. Abbas --- Mohamed J. Mohamed
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2019 Volume: 19 Issue: 3 Pages: 1-15
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

One of the major problems in the field of mobile robots is the trajectory tracking problem. There are a big number of investigations for different control strategies that have been used to control the motion of the mobile robot when the nonlinear kinematic model of mobile robots was considered. The trajectory tracking control of autonomous wheeled mobile robot in a changing unstructured environment needs to take into account different types of uncertainties. Type-1 fuzzy logic sets present limitations in handling those uncertainties while type-2 fuzzy logic sets can manage these uncertainties to give a superior performance. This paper focuses on the design of interval type-2 fuzzy like proportional-integral-derivative (PID) controller for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller’s parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with minimum tracking error. The Matlab simulation results demonstrate the good performance and robustness of this controller. These were confirmed by the obtained values of the position tracking errors and a very smooth velocity, especially with regards to the presence of external disturbance or change in the initial position of mobile robot. Finally, in comparison with other proposed controllers, the results of nonlinear IT2FLC PID controller outperform the nonlinear PID neural controller in minimizing the MSE for all control variables and in the robustness measure.


Article
Information Hiding in Color Image based on LSB and FA
اخفاء المعلومات في صورة ملونة باعتماد تقنية LSB و FA

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Abstract

In this research was to hide information in color images of the type of Joint Photographic Experts Group (JPEG) using hiding technique Least Significant Bit (LSB) with Firefly algorithm. The selection of appropriate image cells for hiding by using Firefly algorithm, then hide one bit of the secret message in least significant bit of all eight block of selected cells . Reached the Peak Signal to Noise Ratio (PSNR) to (78.0892) and the value of the Mean Square Error (MSE) approximately (0.0010), as well as the value of the Bit Error Rate (BER), which was (0).

في هذا البحث تم اخفاء معلومات في صور ملونة من نوعJoint Photographic Experts Group (JPEG) باستخدام الاخفاء بتقنية الخلية الثنائية الاقل اهمية مع خوارزمية حشرة اليراعة . يتم اختيار الخلايا الصورية الملائمة للإخفاء باستخدام خوارزمية حشرة اليراعة , ثم يتم اخفاء خلية ثنائية واحدة من الرسالة السرية في الخلية الثنائية الاقل اهمية من كل كتلة ثمانية من الخلايا الصورية المختارة . وصلت قيمة ذروة الاشارة الى نسبة الضوضاءPeak Signal to Noise Ratio (PSNR) الى (78.0892) وكانت قيمة متوسط مربع الخطأMean Square Error (MSE) ما يقارب (0.0010)، فضلاَ عن قيمة نسبة الخطأ في الرسالة السريةBit Error Rate(BER) التي كانت (0).


Article
A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
دراسة مقارنة لخوارزميات ذكية مختلفة القائمة على تخطيط المسارات لعدد من الروبوتات المتنقلة

Authors: Muna Mohammed Jawad منى محمد جواد --- Esraa Adnan Hadi أسراء عدنان هادي
Journal: Journal of Engineering مجلة الهندسة ISSN: 17264073 25203339 Year: 2019 Volume: 25 Issue: 6 Pages: 83-100
Publisher: Baghdad University جامعة بغداد

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Abstract

In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot. Simulation results, which carried out using MATLAB 2014 environment, show the validity of the kinematic model for Nonholonomic mobile robot and demonstration that the proposed algorithm perform better than original PSO and FF algorithms under the same environmental constraints by providing the smoothness velocity and shortest path for each mobile robot.

بشكل عام تعتبر مشكلة تخطيط المسار واحدة من أهم المهام في مجال الروبوتات. يصف هذا البحث مشكلة تخطيط مسار للروبوتات متحركة استنادا الى خوارزميات الذكاء الاصطناعي المختلفة. ويجب ان يفي مسار الروبوت بعدد من المعايير ومنها طول المسار والسلامة. في هذا البحث يتم تطبيق ثلاثة طرق مختلفة وهي خوارزمية اليرقات المضيئة، خوارزمية سرب الطيور وخوارزمية اليراعات المضيئة وسرب الطيور المشوشة الهجينة المقترحة في بيئة ثابتة ومعروفة لحل مشكلة تخطيط المسارات وبثلاث حالات. في الحالة الأولى، روبوت متنقل واحد، وفي الحالة الثانية، ثلاثة روبوتات متنقلة مستقلة أما في الحالة الثالثة ثلاثة روبوتات متنقلة متتابعة. وتظهر صحة النموذج المستخدم للروبوت المتحرك وتوضح ان الخوارزمية الهجينة المقترحة تؤدي أداء أفضل من خوارزمية سرب الطيور وخوارزمية اليراعات المضيئة تحت نفس الشروط البيئية عن طريق الحصول على سرع سلسة وأقصر مسارات لعدد من الروبوتات المتنقلة.

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