An integrated fuzzy rough set and real coded genetic algorithm approach for crop identification in smart agriculture

2021 ◽  
Author(s):  
D. P. Acharjya ◽  
R. Rathi
Keyword(s):  
Genetic Algorithm ◽  
Rough Set ◽  
Fuzzy Rough Set ◽  
Real Coded Genetic Algorithm ◽  
Genetic Algorithm Approach ◽  
Smart Agriculture

scholarly journals Transport Aircraft Conceptual Design Optimization Using Real Coded Genetic Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Vedant Singh ◽  
Somesh K. Sharma ◽  
S. Vaibhav
Keyword(s):  
Genetic Algorithm ◽  
Conceptual Design ◽  
Air Transport ◽  
Simple Task ◽  
Transport Aircraft ◽  
Air Transport Industry ◽  
Real Coded Genetic Algorithm ◽  
Transport Industry ◽  
Genetic Algorithm Approach ◽  
Aircraft Conceptual Design

Due to soaring oil prices, increased air traffic and competition among air transport companies, and environmental concerns, aircraft maximum takeoff weight (MTOW) is becoming a critical aspect, of air transport industry. It is very important to estimate the MTOW of the aircraft in order to determine its performance. However, estimating the weight of an aircraft is not a simple task. The purpose of this paper is to present a simplified method to optimize the aircraft MTOW using a genetic algorithm approach. For the optimization of MTOW of transport aircraft, a MATLAB program consisting of genetic algorithm techniques with appropriate genetic algorithm parameters setting was developed. The objective function for the optimization was a minimization of MTOW. The use of genetic real coded algorithm (GA) as an optimization tool for an aircraft can help to reduce the number of qualitative decisions. Also, using GA approach, the time and the cost of conceptual design can considerably be reduced. The model is applicable to the air transport industry. The proposed model has been validated against the known configuration of an aircraft.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

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