An Optimization Algorithm Based on Brainstorming Process

2013 ◽  
pp. 137-166
Author(s):  
Yuhui Shi
Keyword(s):  
Optimization Algorithm ◽  
Information Entropy ◽  
The Other ◽  
Future Research ◽  
Brain Storm Optimization ◽  
Cluster Distance ◽  
Simulation Results ◽  
Better Than

In this paper, the human brainstorming process is modeled, based on which two versions of Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance Dc and inter-cluster diversity De are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by Dc and/or De, which points at one direction for future research on BSO algorithms.

An Optimization Algorithm Based on Brainstorming Process

2015 ◽  
pp. 1-35 ◽  
Author(s):  
Yuhui Shi
Keyword(s):  
Optimization Algorithm ◽  
Information Entropy ◽  
The Other ◽  
Future Research ◽  
Brain Storm Optimization ◽  
Cluster Distance ◽  
Simulation Results ◽  
Better Than

In this chapter, the human brainstorming process is modeled, based on which two versions of a Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance Dc and inter-cluster diversity De are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by Dc, which points at one direction for future research on BSO algorithms.

An Optimization Algorithm Based on Brainstorming Process

2011 ◽  
Vol 2 (4) ◽  
pp. 35-62 ◽  
Author(s):  
Yuhui Shi
Keyword(s):  
Optimization Algorithm ◽  
Information Entropy ◽  
The Other ◽  
Future Research ◽  
Brain Storm Optimization ◽  
Cluster Distance ◽  
Simulation Results ◽  
Better Than

In this paper, the human brainstorming process is modeled, based on which two versions of Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance Dc and inter-cluster diversity De are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by Dc and/or De, which points at one direction for future research on BSO algorithms.

Simulation on Effect of Five Kinds of Belt Structures on Tire Performance

2012 ◽  
Vol 501 ◽  
pp. 151-155
Author(s):  
Yong Liu ◽  
Ge Zhang ◽  
Hua Yan ◽  
Yu Mei Ding ◽  
Wei Min Yang
Keyword(s):  
The Other ◽  
Molding Process ◽  
Simulation Results ◽  
Better Than

In this article, three kinds of belt named B, C and D type are invented, then their main performance are compared with the other two kinds of belt structures introduced in previous papers. Simulation results showed that B and D-type belts are better than the other three. Comparatively the latter needs less material, its molding process is easier, and the tire body is lighter than B type tire, so in general it can be considered that D-type belt is the best among the five kinds of belt structures.

Research on a Dynamic Binary Stack Anti-Collision Algorithm

2012 ◽  
Vol 268-270 ◽  
pp. 1426-1431
Author(s):  
Jian Jun Yi ◽  
Fei Luo ◽  
Shao Li Chen ◽  
Bai Yang Ji ◽  
Hai Xu Yan
Keyword(s):  
The Other ◽  
Application System ◽  
Key Technology ◽  
Rfid Systems ◽  
Simulation Results ◽  
Better Than ◽  
Improved Algorithm

RFID anti-collision technology is one of a key technology in RFID application system. Anti-collision algorithms for RFID systems include tag anti-collision algorithms and reader anti-collision algorithms. This paper focused on the impoved binary algorithm and dynamic binary algorithm. An improved algorithm has been proposed, in which the collision bits was put into the stack and they were used as the reader’s request. Based on this mechanism, a novel binary stack algorithm has been proposed. Its simulation was given to analyze the performance of this algorithm. The simulation results showed that the amount of transmitted data in proposed algorithm was obviously less than those in the other two traditional algorithms with the number of tags and their bytes increasing. Consequently, the performance of the proposed algorithm is much better than that of the traditional anti-collision binary algorithm.

scholarly journals Shrinkage of Real Power Loss by Enriched Brain Storm Optimization Algorithm

2019 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Human Being ◽  
New Approach ◽  
Real Power ◽  
Brain Storm Optimization ◽  
Course Of Action ◽  
Simulation Results ◽  
Power Problem

<p class="Author">This paper proposes Enriched Brain Storm Optimization (EBSO) algorithm is used for soving reactive power problem. Human being are the most intellectual creature in this world. Unsurprisingly, optimization algorithm stimulated by human being inspired problem solving procedure should be advanced than the optimization algorithms enthused by collective deeds of ants, bee, etc. In this paper, we commence a new Enriched brain storm optimization algorithm, which was enthused by the human brainstorming course of action. In the projected Enriched Brain Storm Optimization (EBSO) algorithm, the vibrant clustering strategy is used to perk up the k-means clustering process. The most important view of the vibrant clustering strategy is that; regularly execute the k-means clustering after a definite number of generations, so that the swapping of information wrap all ideas in the clusters to accomplish suitable searching capability. This new approach leads to wonderful results with little computational efforts. In order to evaluate the efficiency of the proposed Enriched Brain Storm Optimization (EBSO) algorithm, has been tested standard IEEE 118 &amp; practical 191 bus test systems and compared to other standard reported algorithms. Simulation results show that Enriched Brain Storm Optimization (EBSO) algorithm is superior to other algorithms in reducing the real power loss.</p>

scholarly journals REDUCTION OF TRUE POWER LOSS BY IMPROVED ALGORITHM

2018 ◽  
Vol 6 (8) ◽  
pp. 105-113
Author(s):  
K. Lenin
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
New Approach ◽  
Real Power ◽  
Brain Storm Optimization ◽  
Course Of Action ◽  
Simulation Results ◽  
Power Problem

This paper proposes Improved Brain Storm Optimization (IBSO) algorithm is used for solving reactive power problem. predictably, optimization algorithm stimulated by human being inspired problem-solving procedure should be highly developed than the optimization algorithms enthused by collective deeds of ants, bee, etc. In this paper, a new Improved brain storm optimization algorithm defined, which was stimulated by the human brainstorming course of action. In the projected Improved Brain Storm Optimization (IBSO) algorithm, the vibrant clustering strategy is used to perk up the k-means clustering process & exchange of information wrap all ideas in the clusters to accomplish suitable searching capability. This new approach leads to wonderful results with little computational efforts. In order to evaluate the efficiency of the proposed Improved Brain Storm Optimization (IBSO) algorithm, has been tested standard IEEE 30 bus test system and compared to other standard reported algorithms. Simulation results show that Improved Brain Storm Optimization (IBSO) algorithm is superior to other algorithms in reducing the real power loss.

Performance Evaluation of Different Backoff Algorithms in IEEE 802.15.4 using Double Sensing

2017 ◽  
Vol 5 (2) ◽  
pp. 376
Author(s):  
Md. Mohibur Rahaman ◽  
Mohammad Khairul Islam ◽  
Kazi Ashrafuzzaman ◽  
Mohammad Sanaullah Chowdhury
Keyword(s):  
Performance Evaluation ◽  
Ieee 802.15.4 ◽  
The Other ◽  
Area Network ◽  
Exponential Increase ◽  
Exponential Decrease ◽  
Simulation Results ◽  
Personal Area Network ◽  
Low Rate ◽  
Better Than

<p>The IEEE 802.15.4 is the standard for Low Rate Wireless Personal Area network (LR-WPAN). It is widely used in many application areas. The standard uses Slotted CSMA/CA mechanism in its contention access period (CAP) for the beacon enabled mode. The protocol has two modes - single sensing (SS) and double sensing (DS). The protocol also adopts a binary exponential backoff (BEB) algorithm. In this paper, we explore the saturation throughput, delay and energy consumption of this standard with double sensing (DS) using the existing BEB algorithm. We also investigate three other backoff schemes - exponential increase exponential decrease (EIED), exponential increase linear decrease (EILD) and exponential increase multiplicative decrease (EIMD). From simulation results, it is found that the EIED, EILD, EIMD perform better than the BEB for higher loads. It shows that the EIED, EILD, EIMD have better throughput and lower delay than the BEB. The EIED outperforms the other schemes in terms of throughput, delay and energy for the higher loads.</p>

The Comparison among Three Control Charts for Monitoring the Auto Correlated Processes

2014 ◽  
Vol 490-491 ◽  
pp. 1579-1583
Author(s):  
Ming Jie Yang ◽  
Xue Min Zi
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
The Other ◽  
First Order ◽  
Regressive Model ◽  
Auto Regressive ◽  
The Mean ◽  
Simulation Results ◽  
Auto Regressive Model ◽  
Better Than

We compare the ARL of three charts for monitoring the mean shifts of the first-order auto regressive model to choose a proper control chart. Simulation results show that the REWMA chart has a large superior to the EWMA and T2 the chart when -1<Ø<0, but when Ø>0, the chart is better than the other two charts.

Niche Brain Storm Optimization Algorithm for Multi-Peak Function Optimization

2014 ◽  
Vol 989-994 ◽  
pp. 1626-1630 ◽  
Author(s):  
Heng Jun Zhou ◽  
Ming Yan Jiang ◽  
Xian Ye Ben
Keyword(s):  
Optimization Algorithm ◽  
Population Diversity ◽  
Function Optimization ◽  
Excellent Performance ◽  
Brain Storm Optimization ◽  
Peak Function ◽  
Searching Ability ◽  
Swarm Intelligence Optimization ◽  
Global And Local ◽  
Better Than

Brain Storm Optimization (BSO) is a novel proposed swarm intelligence optimization algorithm which has a fast convergent speed. However, it is easy to trap into local optimal. In this paper, a new model based on niche technology, which is named Niche Brain Storm Optimization (NBSO), is proposed to overcome the shortcoming of BSO. Niche technology effectively prevents premature and maintains population diversity during the evolution process. NBSO shows excellent performance in searching global value and finding multiple global and local optimal solutions for the multi-peak problems. Several benchmark functions are introduced to evaluate its performance. Experimental results show that NBSO performs better than BSO in global searching ability and faster than Niche Genetic Algorithm (NGA) in finding peaks for multi-peak function.

Flood and Substance Transportation Analysis Using Satellite Elevation Data: A Case Study in Dhaka City, Bangladesh

2018 ◽  
Vol 13 (5) ◽  
pp. 967-977 ◽  
Author(s):  
Masakazu Hashimoto ◽  
Nozomu Yoneyama ◽  
Kenji Kawaike ◽  
Tomonori Deguchi ◽  
Mohammed Abed Hossain ◽  
...  
Keyword(s):  
The Other ◽  
Two Dimensional ◽  
Dhaka City ◽  
Flood Simulation ◽  
Aster Gdem ◽  
Elevation Data ◽  
Vertical Accuracy ◽  
Simulation Results ◽  
Better Than

This study investigated the vertical accuracy of satellite elevation data and its effect on flood and substance transportation analysis by using a two-dimensional flood simulation model. SRTM, AW3D, and ASTER GDEM satellite elevation data for East Dhaka, Bangladesh were used for evaluating the vertical accuracy and conducting numerical analyses. A case study in 2007 was simulated for the flooding analysis. The results showed that AW3D had the highest applicability because its vertical accuracy for low-lying areas was better than that of the other products. According to the differences in the flood extent of each satellite elevation data, the simulation results of the substance transportation analysis showed different spreading conditions. Furthermore, differences in the flood velocity and direction affected the distribution of the deposited substance.

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