scholarly journals Autofocusing Optimal Search Algorithm for a Telescope System

2021 ◽  
pp. 2150012
Author(s):  
Islam Helmy ◽  
Alaa Hamdy ◽  
Doaa Eid ◽  
Ahmed Shokry
Keyword(s):  
Search Algorithm ◽  
Search Algorithms ◽  
Binary Search ◽  
Imaging Systems ◽  
Search Process ◽  
Optimal Search ◽  
Astronomical Observations ◽  
Telescope System ◽  
Auto Focusing

Focus accuracy affects the quality of the astronomical observations. Auto-focusing is necessary for imaging systems designed for astronomical observations. The automatic focus system searches for the best focus position by using a proposed search algorithm. The search algorithm uses the image’s focus levels as its objective function in the search process. This paper aims to study the performance of several search algorithms to select a suitable one. The proper search algorithm will be used to develop an automatic focus system for Kottamia Astronomical Observatory (KAO). The optimal search algorithm is selected by applying several search algorithms into five sequences of star-clusters observations. Then, their performance is evaluated based on two criteria, which are accuracy and number of steps. The experimental results show that the Binary search is the optimal search algorithm.

scholarly journals Development Binary Search Algorithm

2011 ◽  
Vol 8 (2) ◽  
pp. 625-629
Author(s):  
Baghdad Science Journal
Keyword(s):  
Search Algorithm ◽  
Search Algorithms ◽  
Binary Search ◽  
Search Process ◽  
Average Case ◽  
Case Complexity ◽  
Average Case Complexity ◽  
Order Of Magnitude ◽  
Binary Search Algorithm ◽  
Search Interval

There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case complexity of Search) is O(log2 n) (pronounce this "big-Oh-n" or "the order of magnitude"), if we search in a list consists of (N) elements. In this research the number of comparison is reduced to triple by using Triple structure, this process makes the maximum number of comparisons is O(log2 (n)/3+1) if we search key in list consist of (N) elements.

scholarly journals Composite Differential Search Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Bo Liu
Keyword(s):  
Convergence Rate ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Control Parameters ◽  
Original Algorithm ◽  
New Space ◽  
Random Method ◽  
Better Than

Differential search algorithm (DS) is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS) is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

Study on Free Search for Combinatorial Optimization Problem

2013 ◽  
Vol 411-414 ◽  
pp. 1904-1910
Author(s):  
Kai Zhong Jiang ◽  
Tian Bo Wang ◽  
Zhong Tuan Zheng ◽  
Yu Zhou
Keyword(s):  
Combinatorial Optimization ◽  
Optimization Problem ◽  
Feasible Solution ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Search Process ◽  
Standard Data ◽  
Combinatorial Optimization Problems ◽  
Free Search

An algorithm based on free search is proposed for the combinatorial optimization problems. In this algorithm, a feasible solution is converted into a full permutation of all the elements and a transformation of one solution into another solution can be interpreted the transformation of one permutation into another permutation. Then, the algorithm is combined with intersection elimination. The discrete free search algorithm greatly improves the convergence rate of the search process and enhances the quality of the results. The experiment results on TSP standard data show that the performance of the proposed algorithm is increased by about 2.7% than that of the genetic algorithm.

scholarly journals COMPARISON OF SOFTWARE COMPLEXITY OF SEARCH ALGORITHM USING CODE BASED COMPLEXITY METRICS

2021 ◽  
Vol 6 (5) ◽  
Author(s):  
Bello Muriana ◽  
Ogba Paul Onuh
Keyword(s):  
Software Engineering ◽  
Programming Languages ◽  
Search Algorithm ◽  
Source Code ◽  
Search Algorithms ◽  
Binary Search ◽  
Software Systems ◽  
Software Complexity ◽  
Complexity Metrics ◽  
Binary Search Algorithm

Measures of software complexity are essential part of software engineering. Complexity metrics can be used to forecast key information regarding the testability, reliability, and manageability of software systems from study of the source code. This paper presents the results of three distinct software complexity metrics that were applied to two searching algorithms (Linear and Binary search algorithm). The goal is to compare the complexity of linear and binary search algorithms implemented in (Python, Java, and C++ languages) and measure the sample algorithms using line of code, McCabe and Halstead metrics. The findings indicate that the program difficulty of Halstead metrics has minimal value for both linear and binary search when implemented in python. Analysis of Variance (ANOVA) was adopted to determine whether there is any statistically significant differences between the search algorithms when implemented in the three programming languages and it was revealed that the three (3) programming languages do not vary considerably for both linear and binary search techniques which implies that any of the (3) programming languages is suitable for coding linear and binary search algorithms.

scholarly journals Penerapan Algoritma Horspool pada Aplikasi Katalog Buku Perpustakaan

2019 ◽  
Vol 1 ◽  
pp. 881
Author(s):  
Fince Tinus Waruwu ◽  
Rivalri Kristianto Hondro
Keyword(s):  
Reference Material ◽  
General Public ◽  
Search Algorithm ◽  
String Matching ◽  
Search Algorithms ◽  
Library Services ◽  
Search Process ◽  
Library Book ◽  
Long Time ◽  
Time And Energy

The library is a place that provides various types of reading books as reference material for students, students, educators and the general public. The library certainly provides various types of books that are different according to their needs. Finding books that are needed in a library with a large number of books certainly takes a long time and energy. In supporting library services and providing convenience for visitors, an application is built that helps visitors find the books they need to not need a long time and effort. In the book catalog application it is necessary to apply a search algorithm (string matching). Search algorithms help enders in finding the books they need. The search algorithm applied to the library book catalog application is the Horspool algorithm. Horspool algorithm is one algorithm that is widely used in the search process. By applying the Horspool algorithm in the library book catalog application can be faster and facilitate the process of finding the title of the book.

scholarly journals Simulated Annealing with Exploratory Sensing for Global Optimization

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 230
Author(s):  
Majid Almarashi ◽  
Wael Deabes ◽  
Hesham H. Amin ◽  
Abdel-Rahman Hedar
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Initial Temperature ◽  
Search Algorithm ◽  
Random Search ◽  
Search Space ◽  
Search Algorithms ◽  
Two Phases ◽  
Number Of Iterations

Simulated annealing is a well-known search algorithm used with success history in many search problems. However, the random walk of the simulated annealing does not benefit from the memory of visited states, causing excessive random search with no diversification history. Unlike memory-based search algorithms such as the tabu search, the search in simulated annealing is dependent on the choice of the initial temperature to explore the search space, which has little indications of how much exploration has been carried out. The lack of exploration eye can affect the quality of the found solutions while the nature of the search in simulated annealing is mainly local. In this work, a methodology of two phases using an automatic diversification and intensification based on memory and sensing tools is proposed. The proposed method is called Simulated Annealing with Exploratory Sensing. The computational experiments show the efficiency of the proposed method in ensuring a good exploration while finding good solutions within a similar number of iterations.

scholarly journals Application of Improved Sparrow Search Algorithm in Concrete

2021 ◽  
Vol 2082 (1) ◽  
pp. 012014
Author(s):  
Chengtian Ouyang ◽  
Feng Tang ◽  
Donglin Zhu ◽  
Yaxian Qiu ◽  
Yujia Liu
Keyword(s):  
Local Search ◽  
High Stability ◽  
Search Algorithm ◽  
Concrete Strength ◽  
Optimal Solution ◽  
Search Algorithms ◽  
Strength Prediction

Abstract Compared with other algorithms, the performance of sparrow algorithm is better, but it also has shortcomings such as insufficient convergence and large randomness. For this reason, this paper proposes an improved sparrow search algorithm, which uses K-means to initialize the population to reduce the influence of randomness. Use sine and cosine search to improve the quality of the position of followers, and finally use adaptive local search to update the optimal solution, and apply it to concrete strength prediction. The results show that various improved sparrow search algorithms have certain advantages and high stability.

Comparing Strategies for Topologic and Parametric Rule Application in Automated Computational Design Synthesis1

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Corinna Königseder ◽  
Kristina Shea
Keyword(s):  
Search Algorithm ◽  
Computational Design ◽  
Search Process ◽  
Graph Grammars ◽  
Design Synthesis ◽  
Design Task ◽  
Rule Application ◽  
Bicycle Frame ◽  
Computational Design Synthesis

Graph grammars are used for computational design synthesis (CDS) in which engineering knowledge is formalized using graphs to represent designs and rules that describe their transformation. Most engineering tasks require both topologic and parametric rules to generate designs. The research presented in this paper compares different strategies for rule application to combine topologic and parametric rules during automated design synthesis driven by a search process. The presented strategies are compared considering quantity and quality of the generated designs. The effect of the strategies, the selected search algorithm, and the initial design, from which the synthesis is started, are analyzed for two case studies: gearbox synthesis and bicycle frame synthesis. Results show that the effect of the strategy is dependent on the design task. Recommendations are given on which strategies to use for which design task.

scholarly journals Exploiting Obstacle Geometry to Reduce Search Time in Grid-Based Pathfinding

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1186
Author(s):  
Fahed Jubair ◽  
Mohammed Hawa
Keyword(s):  
Heuristic Search ◽  
Search Algorithm ◽  
Search Time ◽  
Search Tree ◽  
Search Algorithms ◽  
Binary Search ◽  
Binary Search Tree ◽  
Grid Map ◽  
Heuristic Search Algorithms ◽  
The Impact

Pathfinding is the problem of finding the shortest path between a pair of nodes in a graph. In the context of uniform-cost undirected grid maps, heuristic search algorithms, such as A ★ and weighted A ★ ( W A ★ ), have been dominantly used for pathfinding. However, the lack of knowledge about obstacle shapes in a gird map often leads heuristic search algorithms to unnecessarily explore areas where a viable path is not available. We refer to such areas in a grid map as blocked areas (BAs). This paper introduces a preprocessing algorithm that analyzes the geometry of obstacles in a grid map and stores knowledge about blocked areas in a memory-efficient balanced binary search tree data structure. During actual pathfinding, a search algorithm accesses the binary search tree to identify blocked areas in a grid map and therefore avoid exploring them. As a result, the search time is significantly reduced. The scope of the paper covers maps in which obstacles are represented as horizontal and vertical line-segments. The impact of using the blocked area knowledge during pathfinding in A ★ and W A ★ is evaluated using publicly available benchmark set, consisting of sixty grid maps of mazes and rooms. In mazes, the search time for both A ★ and W A ★ is reduced by 28 % , on average. In rooms, the search time for both A ★ and W A ★ is reduced by 30 % , on average. This is achieved while preserving the search optimality of A ★ and the search sub-optimality of W A ★ .

A Fast Image Encoding Algorithm Based on the Pyramid Structure of Codewords

2009 ◽  
Vol 1 (4) ◽  
pp. 1-13 ◽  
Author(s):  
Ahmed A. Radwan ◽  
Ahmed Swilem ◽  
Mamdouh M. Gomaa
Keyword(s):  
Vector Quantization ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Search Process ◽  
Image Encoding ◽  
Fast Search Algorithm ◽  
Pyramid Structure ◽  
Speed Up ◽  
Simulation Results ◽  
Full Search

This article presents a very simple and efficient algorithm for codeword search in the vector quantization encoding. This algorithm uses 2-pixel merging norm pyramid structure to speed up the closest codeword search process. The authors first derive a condition to eliminate unnecessary matching operations from the search procedure. Then, based on this elimination condition, a fast search algorithm is suggested. Simulation results show that, the proposed search algorithm reduces the encoding complexity while maintaining the same encoding quality as that of the full search algorithm. It is also found that the proposed algorithm outperforms the existing search algorithms.

Sign in / Sign up

Export Citation Format

Share Document