A Novel Multiuser Detector Based on Restricted Search Space and Depth-First Tree Search Method in DS/CDMA Communication Systems

2015 ◽  
Vol 82 (3) ◽  
pp. 1531-1545 ◽  
Author(s):  
Abdulhamid Zahedi ◽  
Sahbasadat Rajamand ◽  
Sajad Jafari ◽  
Mohammad Reza Rajati
Keyword(s):  
Communication Systems ◽  
Search Space ◽  
Search Method ◽  
Tree Search ◽  
Multiuser Detector

RevCuT Tree Search Method in Complex Single-player Game with Continuous Search Space

2019 ◽  
Author(s):  
Hongming Zhang ◽  
Fangjuan Cheng ◽  
Bo Xu ◽  
Feng Chen ◽  
Jiachen Liu ◽  
...  
Keyword(s):  
Search Space ◽  
Search Method ◽  
Tree Search ◽  
Player Game

Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

2017 ◽  
Vol 27 (03) ◽  
pp. 343-372 ◽  
Author(s):  
Umit Can ◽  
Bilal Alatas
Keyword(s):  
Association Rules ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Search Space ◽  
Search Method ◽  
Quantitative Association Rules ◽  
Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

Hardware Efficient Massive MIMO Detector Based on the Monte Carlo Tree Search Method

2017 ◽  
Vol 7 (4) ◽  
pp. 523-533 ◽  
Author(s):  
Jienan Chen ◽  
Chao Fei ◽  
Hao Lu ◽  
Gerald E. Sobelman ◽  
Jianhao Hu
Keyword(s):  
Monte Carlo ◽  
Massive Mimo ◽  
Search Method ◽  
Tree Search ◽  
Monte Carlo Tree Search

Data Clustering Using Sine Cosine Algorithm

2017 ◽  
pp. 715-726 ◽  
Author(s):  
Vijay Kumar ◽  
Dinesh Kumar
Keyword(s):  
Real Life ◽  
Quality Measures ◽  
Search Space ◽  
Search Method ◽  
Local Optima ◽  
Encoding Scheme ◽  
Clustering Techniques ◽  
Sine Cosine Algorithm ◽  
Cluster Quality ◽  
Optimal Cluster

The clustering techniques suffer from cluster centers initialization and local optima problems. In this chapter, the new metaheuristic algorithm, Sine Cosine Algorithm (SCA), is used as a search method to solve these problems. The SCA explores the search space of given dataset to find out the near-optimal cluster centers. The center based encoding scheme is used to evolve the cluster centers. The proposed SCA-based clustering technique is evaluated on four real-life datasets. The performance of SCA-based clustering is compared with recently developed clustering techniques. The experimental results reveal that SCA-based clustering gives better values in terms of cluster quality measures.

scholarly journals Density bounds for the $3x+1$ problem. I. Tree-search method

1995 ◽  
Vol 64 (209) ◽  
pp. 411-411
Author(s):  
David Applegate ◽  
Jeffrey C. Lagarias
Keyword(s):  
Search Method ◽  
Tree Search
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