Automatic Fuzzy Rule Base Generation from Numerical Data: Cuckoo Search Algorithm

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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Fuzzy Rule Base Design With Probabilistic Weights

10.21528/cbic2011-05.3 ◽

2016 ◽

Author(s):

Leonardo G. Melo ◽

Luís A. Lucas ◽

Myriam R. Delgado

Keyword(s):

Fuzzy Rule ◽

Rule Base ◽

Fuzzy Rule Base ◽

Base Design

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Optimized vessel detection in marine environment using hybrid adaptive cuckoo search algorithm

Computers & Electrical Engineering ◽

10.1016/j.compeleceng.2019.08.009 ◽

2019 ◽

Vol 78 ◽

pp. 482-492 ◽

Cited By ~ 1

Author(s):

Iwin Thanakumar Joseph S. ◽

J. Sasikala ◽

D. Sujitha Juliet

Keyword(s):

Marine Environment ◽

Search Algorithm ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Vessel Detection

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Optimizing Voltage Profile and Loss Minimization using Multi Objective Cuckoo Search Algorithm

2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE) ◽

10.1109/iscaie51753.2021.9431835 ◽

2021 ◽

Author(s):

Mohamad Izwan Zainal ◽

Zuhaila Mat Yasin ◽

Zuhaina Zakaria

Keyword(s):

Search Algorithm ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Voltage Profile ◽

Loss Minimization ◽

Multi Objective

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Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01951-1 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Yang Wang ◽

Feifan Wang ◽

Yujun Zhu ◽

Yiyang Liu ◽

Chuanxin Zhao

Keyword(s):

Sensor Network ◽

Sensor Node ◽

Search Algorithm ◽

Optimal Solution ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Sensor Nodes ◽

Optimization Strategy ◽

Multi Objective ◽

Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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