An Improved D-S Evidence Theory Based on Genetic Algorithm to VIP Intelligent Recognition and Recommendation System

2013 ◽  
Vol 347-350 ◽  
pp. 2442-2446
Author(s):  
Xiao Yin Xu ◽  
Li Hong Ren ◽  
Yong Sheng Ding
Keyword(s):  
Genetic Algorithm ◽  
Body Size ◽  
Recommendation System ◽  
Evidence Theory ◽  
Suitable Method ◽  
Improved Method ◽  
The Stability ◽  
Intelligent Recognition

In this paper, we use GA to improve the D-S evidence theory, and apply the improved D-S evidence theory to VIP intelligent recognition and recommendation system. In the VIP intelligent recognition and recommendation system of clothes, there are three main evidences: body size, personal preferences, and purchase records. So collision often happens inevitable. This requirement asks us to find out a suitable method to identify the VIPs needs. D-S evidence theory can improve the rate of identification, but has no idea about the collision. The improved D-S evidence theory based on genetic algorithm can deal with the collision evidence and improve the rate of the identification and the stability. As such we can provide VIP more suitable recommendation. The experiment results of clothes recommendation demonstrate the flexibility of the improved method.

The Influence of Current Speed, Body Size and Water Temperature On the Filtration Rate of Five Species of Bivalves

1972 ◽  
Vol 52 (2) ◽  
pp. 345-374 ◽  
Author(s):  
P. R. Walne
Keyword(s):  
Body Size ◽  
Water Temperature ◽  
Filtration Rate ◽  
Current Speed ◽  
Suitable Method ◽  
Water Filtration ◽  
Water Current ◽  
Water Requirements ◽  
Important Species ◽  
Shellfish Culture

The rate of water filtration by bivalves has long excited interest, but it has in practice proved difficult to measure in conditions where the animal is relatively free from constraint. Its estimation is important from a number of aspects: feeding studies; as an indicator of the animal's reaction to its environment; and for predicting the flow of water required for the culture of economically important species. The work reported in this paper started as part of the general programme on shellfish culture in progress at this laboratory. During the development of a suitable method for studying the water requirements it became clear that one factor, water current, had a more important influence than has been generally recognized.

scholarly journals Optimizing Smartphone Recommendation System through Adaptation of Genetic Algorithm and Progressive Web Application

2021 ◽  
Vol 12 (12) ◽  
Author(s):  
Khyrina Airin Fariza Abu Samah ◽  
Nursalsabiela Affendy Azam ◽  
Raseeda Hamzah ◽  
Chiou Sheng Chew ◽  
Lala Septem Riza
Keyword(s):  
Genetic Algorithm ◽  
Web Application ◽  
Recommendation System

scholarly journals Optimization and comparative analysis of PID and FOPID controller for BLDC motor

2019 ◽  
Vol 8 (3) ◽  
pp. 174
Author(s):  
P. Vimala ◽  
C. R. Balamurugan ◽  
A. Subramanian ◽  
T. Vishwanath
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Input Signal ◽  
Pid Controller ◽  
Input Voltage ◽  
Bldc Motor ◽  
Phase Inverter ◽  
Three Phase ◽  
The Stability ◽  
Three Phase Inverter

The FOPID and PID controller are designed to control the speed of <br /> the BLDC motor. The parameters , , , λ and µ of these controller are optimized based on genetic algorithm. The optimized coefficients keep in track with zero error signals. The output of the controller is given to the variable dc source which varies the input voltage to the three phase inverter depending on the input signal. The three phase inverter gives the voltage to the BLDC motor which enhances the stability of the system. <br /> The effectiveness of the controller is demonstrated by simulation.

Stable Assembly Sequence Planning Using a Genetic Algorithm

1999 ◽  
Author(s):  
Shiang-Fong Chen ◽  
Xiao-Yun Liao
Keyword(s):  
Genetic Algorithm ◽  
Simple Structure ◽  
Fitness Function ◽  
Assembly Sequence Planning ◽  
Connection Matrix ◽  
Assembly Sequence ◽  
Sequence Planning ◽  
Industry Standard ◽  
Planning Algorithm ◽  
The Stability

Abstract Stability problems in assembly sequence planning have drawn great research interest in recent years. Most proposed methodologies are based on graph theory and involve complex geometric and physical analyses. As a result, even for a simple structure, it is difficult to take all the criteria into account and to implement real world solutions. This paper uses a genetic algorithm (GA) to synthesize different criteria fo generating a stable assembl plan. Three matrices (Connection Matrix, Supporting Matrix, and Interference-Free Matrix) are generated from an input B-rep file to represent the CAD information of a given product. The stability of a given assembly plan and reorientation numbers are incorporated into the fitness function of the genetic assembly planner. The proposed planning algorithm has been successfull implemented. This paper also presents implemented planne performance as measured for two industry-standard structures.

scholarly journals Design optimization of multi-objective proportional–integral–derivative controllers for enhanced handling quality of a twin-engine, propeller-driven airplane

2020 ◽  
Vol 12 (6) ◽  
pp. 168781402092317
Author(s):  
Mohsen Rostami ◽  
Joon Chung ◽  
Hyeong Uk Park
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Proportional Integral Derivative ◽  
Optimum Result ◽  
Proportional Integral ◽  
Multi Objective ◽  
Directional Motion ◽  
The Stability ◽  
Handling Quality

Herein, the design optimization of multi-objective controllers for the lateral–directional motion using proportional–integral–derivative controllers for a twin-engine, propeller-driven airplane is presented. The design optimization has been accomplished using the genetic algorithm and the main goal was to enhance the handling quality of the aircraft. The proportional–integral–derivative controllers have been designed such that not only the stability of the lateral–directional motion was satisfied but also the optimum result in longitudinal trim condition was achieved through genetic algorithm. Using genetic algorithm optimization, the handling quality was improved and placed in level 1 from level 2 for the proposed aircraft. A comprehensive sensitivity analysis to different velocities, altitudes and centre of mass positions is presented. Also, the performance of the genetic algorithm has been compared to the case where the particle swarm optimization tool is implemented. In this work, the aerodynamic coefficients as well as the stability and control derivatives were predicted using analytical and semi-empirical methods validated for this type of aircraft.

The stability of the yolk granules of Artemia. An improved method for their isolation and study

1981 ◽  
Vol 10 (6) ◽  
pp. 343-356 ◽  
Author(s):  
Carmen G. Vallejo ◽  
Rosario Perona ◽  
Rafael Garesse ◽  
Roberto Marco
Keyword(s):  
Improved Method ◽  
Yolk Granules ◽  
The Stability

Personalized query recommendation system : A genetic algorithm approach

2020 ◽  
Vol 23 (2) ◽  
pp. 523-535 ◽  
Author(s):  
Debaditya Barman ◽  
Ritam Sarkar ◽  
Anil Tudu ◽  
Nirmalya Chowdhury
Keyword(s):  
Genetic Algorithm ◽  
Recommendation System ◽  
System A ◽  
Query Recommendation ◽  
Genetic Algorithm Approach
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