Simulation and Optimization of 89Zr Radionuclide Production Using Fuzzy Logic and Firefly Algorithm

2021 ◽  
Author(s):  
Peyman Derikvand ◽  
Ali Jamali Nazari ◽  
Mohammadali Ranjbar ◽  
Saeed Zare Ganjaroodi
Keyword(s):  
Fuzzy Logic ◽  
Firefly Algorithm ◽  
Radionuclide Production ◽  
Simulation And Optimization

Intelligent fuzzy logic with firefly algorithm and particle swarm optimization for semi-active suspension system using magneto-rheological damper

2016 ◽  
Vol 23 (3) ◽  
pp. 501-514 ◽  
Author(s):  
Mat Hussin Ab Talib ◽  
Intan Zaurah Mat Darus
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Firefly Algorithm ◽  
Ride Comfort ◽  
Particle Swarm ◽  
Mr Damper ◽  
Suspension System ◽  
System Response ◽  
Swarm Optimization ◽  
Magneto Rheological

This paper presents a new approach for intelligent fuzzy logic (IFL) controller tuning via firefly algorithm (FA) and particle swarm optimization (PSO) for a semi-active (SA) suspension system using a magneto-rheological (MR) damper. The SA suspension system’s mathematical model is established based on quarter vehicles. The MR damper is used to change a conventional damper system to an intelligent damper. It contains a magnetic polarizable particle suspended in a liquid form. The Bouc–Wen model of a MR damper is used to determine the required damping force based on force–displacement and force–velocity characteristics. The performance of the IFL controller optimized by FA and PSO is investigated for control of a MR damper system. The gain scaling of the IFL controller is optimized using FA and PSO techniques in order to achieve the lowest mean square error (MSE) of the system response. The performance of the proposed controllers is then compared with an uncontrolled system in terms of body displacement, body acceleration, suspension deflection, and tire deflection. Two bump disturbance signals and sinusoidal signals are implemented into the system. The simulation results demonstrate that the PSO-tuned IFL exhibits an improvement in ride comfort and has the smallest MSE for acceleration analysis. In addition, the FA-tuned IFL has been proven better than IFL–PSO and uncontrolled systems for both road profile conditions in terms of displacement analysis.

scholarly journals Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5526 ◽  
Author(s):  
Hamza Fahim ◽  
Wei Li ◽  
Shumaila Javaid ◽  
Mian Muhammad Sadiq Fareed ◽  
Gulnaz Ahmed ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Firefly Algorithm ◽  
Fitness Function ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Routing Scheme ◽  
Region Selection ◽  
End To End Delay ◽  
Selection Of

An intrabody nanonetwork (IBNN) is composed of nanoscale (NS) devices, implanted inside the human body for collecting diverse physiological information for diagnostic and treatment purposes. The unique constraints of these NS devices in terms of energy, storage and computational resources are the primary challenges in the effective designing of routing protocols in IBNNs. Our proposed work explicitly considers these limitations and introduces a novel energy-efficient routing scheme based on a fuzzy logic and bio-inspired firefly algorithm. Our proposed fuzzy logic-based correlation region selection and bio-inspired firefly algorithm based nano biosensors (NBSs) nomination jointly contribute to energy conservation by minimizing transmission of correlated spatial data. Our proposed fuzzy logic-based correlation region selection mechanism aims at selecting those correlated regions for data aggregation that are enriched in terms of energy and detected information. While, for the selection of NBSs, we proposed a new bio-inspired firefly algorithm fitness function. The fitness function considers the transmission history and residual energy of NBSs to avoid exhaustion of NBSs in transmitting invaluable information. We conduct extensive simulations using the Nano-SIM tool to validate the in-depth impact of our proposed scheme in saving energy resources, reducing end-to-end delay and improving packet delivery ratio. The detailed comparison of our proposed scheme with different scenarios and flooding scheme confirms the significance of the optimized selection of correlated regions and NBSs in improving network lifetime and packet delivery ratio while reducing the average end-to-end delay.

scholarly journals Mobile Sink in Fuzzy Logic and Meta-heuristic Firefly Algorithm based Routing Scheme to Extend Network Lifetime of WSN (MSFLMFLA)

2021 ◽  
Author(s):  
Pranali Rajendea Navghare ◽  
Sudhakar Pandey ◽  
Deepika Agrawal
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Firefly Algorithm ◽  
Mobile Sink ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Clustering ◽  
Routing Scheme

Abstract Nowadays, wireless sensor network (WSN) improves people's lives by assisting them with a variety of applications. The major challenge in WSN is consumption of power as well as lifetime of the network. Clustering is the important method for saving energy in WSN because the separation of the sender and the receiver is related to transmission energy. In this paper we used fuzzy rules for clustering. Wireless sensor networks are susceptible to energy holes, in which sensors nearer to a static sink rapidly lose energy. To solve this problem and extend network life we used a mobile sink (MS). In this paper, a customized mobile sink node called the mobile data sender (MDS) has been tried to introduce for collecting data from the sensors by going to visit every node and then going to send this to the base station. This paper proposes nature inspired heuristic discrete firefly algorithm to optimal way accumulate information from sensor nodes in order to decrease the path travelled by the MDS while doing the tour. So, in this paper, we consider Mobile Sink in Fuzzy Logic and Meta-heuristic Firefly Algorithm based routing scheme to extend network lifetime of WSN (MSFLMFLA). Here we compare throughput and network lifetime with the static sink in FLMFLA and EHR-DC and LEACH protocol. The results of simulation shows that the MSFLMFLA increases the throughput, residual energy and also increases the data received by the sink.

Modeling, Simulation and Optimization of agricultural greenhouse microclimate by the application of artificial intelligence and / or fuzzy logic

2016 ◽  
Author(s):  
Didi Faouzi ◽  
Nacereddine Bibi-Triki
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
New Technologies ◽  
Eating Habits ◽  
Thermal Evolution ◽  
Supply And Demand ◽  
Weather Conditions ◽  
Thermal Inversion ◽  
Simulation And Optimization ◽  
Greenhouse Growers

Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia. The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost[14-22]. Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying[12-13]. The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and them factors are light, temperature and relative humidity[8]. This state of thermal evolution is the level sealing of the cover of its physical characteristics to be transparent to solar, absorbent and reflective of infrared radiation emitted by the enclosure where the solar radiation trapping effect otherwise called "greenhouse effect" and its technical and technological means of air that accompany. The socio-economic analysis of populations in the world leaves appear especially the last two decades of rapid and profound transformations These changes are accompanied by changes in eating habits, mainly characterized by rising consumption spread along the year[14]. To effectively meet this demand, greenhouse-systems have evolved, particularly towards greater control of production conditions (climate, irrigation, ventilation techniques, CO2 supply, etc ...). Technological progress has allowed the development of greenhouses so that they become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc ...). New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence[10-11] such as neural networks and / or fuzzy logic, etc... As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year.

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