scholarly journals Determinition of best set of adjustable parameters with full search and limited search methods

2013 ◽  
Vol 2 (1) ◽  
pp. 11-14 ◽  
Author(s):  
Ivars Mozga
Keyword(s):  
2011 ◽  
Vol 109 ◽  
pp. 523-527 ◽  
Author(s):  
Zhong Xiu Yang ◽  
Xiao Bo Ren ◽  
Jia Tao Song ◽  
Wan Liang Wang

This paper studied the schedule of lift-sliding stereo garages and proposed an effective schedule based on A* algorithm. The results show that the run time of the schedule based on A* algorithm is almost close to 0. It could effectively work in lift-sliding garages and is better than those full search methods such as simple depth-first search and so on. It solves some problems that exist in the management of stereo garages.


2003 ◽  
Author(s):  
Mark A. Abramson ◽  
Olga A. Brezhneva ◽  
Jr Dennis ◽  
J. E.

Author(s):  
Hafiz Munsub Ali ◽  
Jiangchuan Liu ◽  
Waleed Ejaz

Abstract In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources.


2021 ◽  
Vol 125 (2) ◽  
pp. 1578-1591
Author(s):  
Logan Lang ◽  
Adam Payne ◽  
Irais Valencia-Jaime ◽  
Matthieu J. Verstraete ◽  
Alejandro Bautista-Hernández ◽  
...  

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1970
Author(s):  
Jun-Kyu Park ◽  
Suwoong Lee ◽  
Aaron Park ◽  
Sung-June Baek

In spectroscopy, matching a measured spectrum to a reference spectrum in a large database is often computationally intensive. To solve this problem, we propose a novel fast search algorithm that finds the most similar spectrum in the database. The proposed method is based on principal component transformation and provides results equivalent to the traditional full search method. To reduce the search range, hierarchical clustering is employed, which divides the spectral data into multiple clusters according to the similarity of the spectrum, allowing the search to start at the cluster closest to the input spectrum. Furthermore, a pilot search was applied in advance to further accelerate the search. Experimental results show that the proposed method requires only a small fraction of the computational complexity required by the full search, and it outperforms the previous methods.


2017 ◽  
Vol 78 (3) ◽  
pp. 911-928 ◽  
Author(s):  
Saman Babaie–Kafaki ◽  
Saeed Rezaee

2007 ◽  
Vol 38 (8) ◽  
pp. 1-10
Author(s):  
Tadashi Yamaura ◽  
Hirohisa Tasaki ◽  
Shinya Takahashi
Keyword(s):  

Author(s):  
Shogo Takeuchi ◽  
Tomoyuki Kaneko ◽  
Kazunori Yamaguchi

Sign in / Sign up

Export Citation Format

Share Document