CNN based Heuristic Function for A* Pathfinding Algorithm: Using Spatial Vector Data to Reconstruct Smooth and Natural Looking Plant Roots

In this work we propose an extension to recent methods for the reconstruction of root architectures in 2-dimensions. Recent methods for the automatic root analysis have proposed deep learned segmentation of root images followed by path finding such as Dijkstra’s algorithm to reconstruct root topology. These approaches assume that roots are separate, and that a shortest path within the image foreground represents a reliable reconstruction of the underlying root structure. This approach is prone to error where roots grow in close proximity, with path finding algorithms prone to taking “short cuts” and overlapping much of the root material. Here we extend these methods to also consider root angle, allowing a more informed shortest path search that disambiguates roots growing close together. We adapt a CNN architecture to also predict the angle of root material at each foreground position, and utilise this additional information within shortest path searchers to improve root reconstruction. Our results show an improved ability to separate clustered roots.

Optimization of modes of the electric power systems by genetic algorithms

In article discusses issues for solving optimization problems based on the use of genetic algorithms. Nowadays, the genetic algorithms for solving various problems. This includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc.

Accelerating Traffic Assignment with Customizable Contraction Hierarchies

In many algorithms for traffic assignment, the most time-consuming step is shortest path search between all O–D pairs. Almost unnoticed by the transport modeling community, there has been an enormous amount of research on acceleration techniques for the shortest path problem in road networks in the past decade. These techniques usually divide the problem into a relatively expensive preprocessing phase and a significantly accelerated search phase. In this paper, the recently developed customizable contraction hierarchies are used for both shortest path search and network loading in the bi-conjugate Frank–Wolfe algorithm. For the largest test network, this approach achieves a speedup by a factor of 42 compared with a straightforward implementation of Dijkstra’s algorithm.

Perbandingan Perhitungan Manual dengan Algoritma A Star dalam Pencarian Jalur Terpendek untuk Pengiriman Pesan Dodol Khas Lombok

Abstrak Petugas pengiriman pesanan yang ada PT Phonix melakukan pengiriman pesanan dari gudang ke gerai gerai yang ada di kota mataram dengan melewati atau melintasi jalan yang sama, untuk meminimalkan jarak dan tujuan yang akan dituju maka diperlukan pencarian jalur terpendek dari gudang ke gerai gerai tujuan yang ada dikota mataram. Pencarian jalur terpendek adalah solusi yang tepat untuk mengirimkan pesanan dodol khas lombok ke pelanggan yang ada dikota mataram. Pencarian jalur terpendek pada penelitian ini bertujuan supaya dapat menentukan jalur mana yang paling cepat untuk dilalui atau dilintasi. Algoritma A* adalah salah satu metode yang bisa digunakan untuk pencarian jalur terpendek, dengan menggunakan metode ini diharapkan petugas pengiriman pesanan yang ada gudang dapat lebih cepat menemukan jalur mana yang paling dekat dan lebih cepat untuk menemukan goal pada pencarian jalur terpendek dalam proses pengiriman pesanan pelanggan dodol di daerah lombok dengan menggunakan algoritma A*. Dari penelitian ini melakukan dua proses pengujian yaitu pengujian menggunakan perhitungan manual dan pengujia menggunakan algoritma A*, dari pengujian secara manaual didapatkan jalur terpendek 15.750 dan dengan menggunakan algoritma A* didapatkan jalur terkecil 14.500, hingga pencarian dengan menggunakan perhitungan algoritma cukup biak. Abstract Existing order dispatcher PT Phonix orders shipments from the warehouse to outlets in the city of Mataram by passing or crossing the same road, to minimize the distance and destination to be addressed it is necessary to find the shortest path from the warehouse to the destination outlets in the city mataram. The shortest path search is the right solution for sending dodol orders typical to Lombok to customers in the city of Mataram. The search for the shortest path in this study aims to determine which path is the fastest to be traversed or crossed. Algorithm A * is one method that can be used to search for the shortest path, by using this method it is hoped that an order delivery officer in an existing warehouse can more quickly find the path which is the closest and faster to find a goal in the search for the shortest path in the process of sending customer orders dodol in the Lombok area using the A * algorithm. From this study conducted two testing processes, namely testing using manual calculations and testing using the A * algorithm, from which in the test obtained the shortest path of 15,750 and using the A * algorithm obtained the smallest path of 14,500, to the search using a fairly multiply algorithm calculation.

Optimization of Shortest-Path Search on RDBMS-Based Graphs

Calculation of the shortest path between two nodes in a graph is a popular operation used in graph queries in applications such as map information systems, social networking services, and biotechnology. Recent shortest-path search techniques based on graphs stored in relational databases are able to calculate the shortest path efficiently, even in large data using frontier-expand-merge operations. However, previous approaches used a sequential bidirectional search method that causes a bottleneck, thus degrading performance. The repeated use of an aggregate SQL function also degrades performance. This paper proposes a parallel bi-directional search method using multithreading. In addition, an efficient optimization method is proposed that uses B-tree indexing instead of an aggregate SQL function. Various experiments using synthetic and real data reveal that the proposed optimization technique performs more efficiently than conventional methods. As the size of data in practical applications continues to grow, these optimizations will enable the shortest path in a graph to be found quickly and accurately.

OPTIMIZATION OF MODES OF ELECTR POWER SYSTEMS BY GENETIC ALGOROTHMS

In article discusses issues for solving optimization problems based on the use of genetic algorithms. To date, the genetic use algorithm for solving various problems. Which includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc. As well as the presentation, the selected structure should take into account all the features and limitations imposed on the desired solution, as well as the fact that the implementation of crossоver and mutation algorithms directly depends on its choice. To solve optimization problems, a block diagram of the genetic algorithm is given.