The Joint Use of the Breadth-First Search Strategy and the Constraints Propagation in Smart Tables Handling

2021 ◽  
Author(s):  
Alexander Anatolyevich Zuenko
2008 ◽  
Vol 17 (02) ◽  
pp. 303-320 ◽  
Author(s):  
WEI SONG ◽  
BINGRU YANG ◽  
ZHANGYAN XU

Because of the inherent computational complexity, mining the complete frequent item-set in dense datasets remains to be a challenging task. Mining Maximal Frequent Item-set (MFI) is an alternative to address the problem. Set-Enumeration Tree (SET) is a common data structure used in several MFI mining algorithms. For this kind of algorithm, the process of mining MFI's can also be viewed as the process of searching in set-enumeration tree. To reduce the search space, in this paper, a new algorithm, Index-MaxMiner, for mining MFI is proposed by employing a hybrid search strategy blending breadth-first and depth-first. Firstly, the index array is proposed, and based on bitmap, an algorithm for computing index array is presented. By adding subsume index to frequent items, Index-MaxMiner discovers the candidate MFI's using breadth-first search at one time, which avoids first-level nodes that would not participate in the answer set and reduces drastically the number of candidate itemsets. Then, for candidate MFI's, depth-first search strategy is used to generate all MFI's. Thus, the jumping search in SET is implemented, and the search space is reduced greatly. The experimental results show that the proposed algorithm is efficient especially for dense datasets.


Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 833
Author(s):  
Veera Boonjing ◽  
Pisit Chanvarasuth

This paper formulates the problem of determining all reducts of an information system as a graph search problem. The search space is represented in the form of a rooted graph. The proposed algorithm uses a breadth-first search strategy to search for all reducts starting from the graph root. It expands nodes in breadth-first order and uses a pruning rule to decrease the search space. It is mathematically shown that the proposed algorithm is both time and space efficient.


2013 ◽  
Vol 303-306 ◽  
pp. 2157-2160
Author(s):  
Xin Yi Chen ◽  
Jian Hua Xia

With the expansion of network and the increasing number of communities’ network, It’s a big problem for the search algorithm to enhance the search efficiency. The number of search steps and the amount of query information generated by maximum degree search strategy, which will grow exponentially, consequently, and lead to low the efficiency of search. Without considering the network congestion, breadth-first search strategy is undoubtedly the best search efficiency. From the point of the breadth-first search strategy, this paper designed and proposed the synchronous search strategy of Maximum degree and Bisection degree, and described the algorithm idea and algorithm design for MBDS. The simulation results showed that MBDS not only decreased the amount of query information, but also can efficiently decrease the search steps and improve the search speed.


2000 ◽  
Vol 10 (4) ◽  
pp. 397-408 ◽  
Author(s):  
MICHAEL SPIVEY

Every functional programmer knows the technique of “replacing failure by a list of successes” (Wadler, 1985), but wise programmers are aware also of the possibility that the list will be empty or (worse) divergent. In fact, the “lists of successes” technique is equivalent to the incomplete depth-first search strategy used in Prolog.At heart, the idea is quite simple: whenever we might want to use a ‘multi-function’ such as ‘f’ [ratio ][ratio ] α [Rarr ] β that can return many results or none, we replace it by a genuine function f [ratio ][ratio ] α → β stream that returns a lazy stream of results, and rely on lazy evaluation to compute the answers one at a time, and only as they are needed. For the sake of clarity, I will distinguish between the types of finite lists (α list) and of potentially infinite, lazy streams (α stream), though both may be implemented in the same way. Following the conventions used in ML, type constructors follow their argument types.


2014 ◽  
Vol 556-562 ◽  
pp. 5348-5351
Author(s):  
Bo Cheng

As the computer science is developing rapidly, the search of technology of graphs has emerged in logic, linguistics, chemistry, electronics and some other fields of science. Especially with the rapid development of network technology as well as the appearance of parallel computer, parallel processing is brought into an unprecedented prosperity. And graphs traversal also starts playing a vital role. Breadth-first-search is a fundamental problem of graph theory as well as a heated problem. The parallelization of breadth-first-search has been a tough problem yet to be solved.


1993 ◽  
Vol 03 (03) ◽  
pp. 209-222 ◽  
Author(s):  
RAYMOND GREENLAW

The parallel complexity of a search strategy that combines attributes of both breadth-first search and depth-first search is studied. The search called breadth-depth search was defined by Horowitz and Sahni. The search technique has applications in branch-and-bound strategies. Kindervater and Lenstra posed the complexity of this type of search strategy as an open problem. We resolve their question by showing that a natural decision problem based on breadth-depth search is [Formula: see text]-complete. Specifically, we prove that if given a graph G=(V, E) either directed or undirected, a start vertex s∈V, and two designated vertices u and v in V, then the problem of deciding whether u is visited before v by a breadth-depth search originating from s is [Formula: see text]-complete. The search can be based either on vertex numbers or fixed ordered adjacency lists. Our reductions differ for directed/undirected graphs and depending on whether vertex numbers/fixed ordered adjacency lists are used. These results indicate breadth-depth search is highly sequential in nature and probably will not adapt to a fast parallel solution, unless [Formula: see text] equals [Formula: see text].


2012 ◽  
Vol 82 (4) ◽  
pp. 237-259 ◽  
Author(s):  
Moshe Ben-Shoshan

This review summarizes studies discussing vitamin D status in adults and reveals that vitamin D deficiency/insufficiency is highly prevalent in adults and that current fortification and supplementation policies are inadequate. Background and aims: Studies suggest a crucial role for adequate vitamin D status in various health conditions including bone metabolism, cancer, cardiovascular diseases, and allergies. However, relatively little is known about poor vitamin D status and unmet needs in adults. This report aims to highlight the contribution of epidemiologic studies (through the identification of health effects and societal burden) to the development of vitamin D fortification and supplementation policies and reveal unmet global challenges in adults. Methods: In order to assess worldwide vitamin D status in adults, the search strategy combined the medical literature database MEDLINE (using PubMed) for the time period between January 1, 1980 and February 28, 2011, using the key words “vitamin D” “deficiency” and “insufficiency”, and included articles in which access to full text was possible and in which healthy adults were assessed according to one of four commonly used vitamin D threshold classifications. Results: This report reveals that vitamin D deficiency occurs in 4.10 % [95 % CI (confidence interval), 3.93 %, 4.27 %] to 55.05 % (54.07 %, 56.03 %) of adults, while insufficiency occurs in 26.07 % (24.82 %, 27.33 %) to 78.50 % (77.85 %, 79.16 %), depending on the classification used. However, lack of overlap in CIs and high value of I2 statistics indicate considerable heterogeneity between studies. Further, certain populations (i. e. dark-skinned individuals, immigrants, and pregnant women) may be at higher risk for poor vitamin D status. Conclusion: Current policies for vitamin D supplementation and fortification are inadequate and new guidelines are required to improve vitamin D status in adults.


Author(s):  
Muhammad Aria

Abstrak – Pada penelitian ini dirancang algoritma alternatif untuk perencanaan jalur kendaraan otonom. Algoritma yang diusulkan adalah hibridisasi dari algoritma Breadth First Search (BFS) dan algoritma path smoothing (BFS – path smoothing). Berdasarkan pengamatan dari hasil pengujian, keuntungan dari algoritma BFS adalah dapat memberikan solusi yang menuju solusi optimal, tetapi memiliki kelemahan dari waktu komputasi yang tinggi. Agar diperoleh solusi yang optimal, maka jalur yang dihasilkan oleh algoritma BFS akan diproses lebih lanjut oleh algoritma path smoothing. Walaupun algoritma BFS - path smoothing memiliki waktu komputasi yang tinggi, tetapi untuk tujuan mendapatkan solusi yang optimal, waktu komputasi BFS – path smoothing masih lebih rendah daripada algoritma RRT* untuk mendapatkan solusi yang optimal. Algoritma RRT* adalah salah satu algoritma yang umum digunakan untuk perencanaan jalur pada kendaraan otonom. Proses hibridisasi ini dilakukan dengan cara menjalankan algoritma BFS terlebih dahulu untuk memberikan solusi awal. Solusi awal tersebut kemudian ditingkatkan kualitasnya menggunakan algoritma path smoothing untuk memperoleh solusi yang optimal. Pengujian algoritma BFS-path smoothing ini dilakukan secara simulasi menggunakan beberapa kasus benchmark yang ada, yaitu lingkungan narrow, maze, trap dan clutter. Kriteria optimalitas yang dibandingkan adalah biaya jalur dan waktu komputasi. Pada pengujian, performansi dari algoritma BFS-path smoothing dibandingkan dengan performansi dari algoritma RRT*. Kami menunjukkan bahwa algoritma yang diusulkan dapat menghasilkan output jalur dengan kualitas yang lebih tinggi daripada jalur yang diproduksi oleh RRT*.   Kata Kunci : Beadth First Search, path smoothing, perencanaan jalur, pengujian simulasi, RRT*


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