On the application of graph theory to computer data structure by R.Williams.Robin Williams. On the application of graph theory to computer data structures. In: Computer Graphics 70; an international symposium. Brunei University.Williams, R. On the application of graph theory to computer data ...
Key findings in this review show the size of data as a classification criterion and as data sizes for clustering become larger and varied, the determination of the optimal number of clusters will require new feature extracting methods, validation indices and clustering techniques. In addition, ...
Integrated, timely data about pavement structures, materials and performance information are crucial for the continuous improvement and optimization of pavement design by the engineering research community. However, at present, pavement structures, mater
As the State Grid Multi-cloud IoT platform grows and improves, an increasing number of IoT applications generate massive amounts of data every day. To meet the demands of intelligent management of State Grid equipment, we proposed a scheme for constructing the defect knowledge graph of power equi...
It is commonly known that a number of variables, including price, supply levels, time, and green level, affect how quickly certain things are in demand. Furthermore, the inventory carrying cost is considered to be a nonlinear representation of time and i
Continuing the construction idea in 2.1, we tried to build a set of multi-level graph structure, and split the "representative requirements" and "scenario requirements" into independent levels, which avoided the combination of two types of requirements in the same level. It can cause confusion, ...
In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this pa
Machine learning, a branch of artificial intelligence relying on mathematical and statistical principles, uses sets of data to build models that can perform specific tasks of interest and help accelerate or improve human decision making. In recent years, machine learning has successfully been used to...
Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive ...
Graph theory [27], [28] is a widely used mathematical theorem in computer science, and various local graph structures that generate features have been published in the literature. In this work, we used the Petersen graph [29], which is a specific graph that identifies moduli space on the ...