Search results for "A* algorithm"

Reliability Analysis of a Controlled Stage-Constructed and Reinforced Embankment on Soft Ground Using 2D and 3D Models

2020

Geosynthetic reinforcement has become a very practical technique to improve geotechnical structure safety. In spite of improved soil behavior, structures are affected by uncertainties related to soil and reinforcement material properties. This paper aims to present a reliability analysis in order to take statistical information (uncertainties) into account in a safety analysis of reinforced embankments. The analysis was used in a case study on a controlled stage-constructed embankment on soft ground in order to investigate its probabilistic stability. Modeling was performed by commercial geotechnical software usage (GeoStudio and RocScience packs, SIGMA/W+SLOPE/W and SLIDE³, respectively) a…

Forest road planning to improve tourism accessibility: a comparison of different methods applied in a real case study

2022

Forest road planning with the available tools, e.g. PEGGER and GIS, still requires a lot of time of an expert, and the designed roads are not guaranteed to be efficient in terms of the cost or suitability of the road. In this article, we propose a novel Genetic Algorithm (GA) based method for forest road planning. To do so, each road is represented as a sequence of fixed and variable (control) points. A novel objective (fitness) function is defined based on the length, gradient, and suitability of the roads (individuals). The proposed algorithm is applied to the Arasbaran forest area and the resulted roads are compared with PEGGER-designed roads regarding length, Bachmund index, accessibili…

Melanoma Clinics and Treatment

2013

Exact simulation of first exit times for one-dimensional diffusion processes

2019

International audience; The simulation of exit times for diffusion processes is a challenging task since it concerns many applications in different fields like mathematical finance, neuroscience, reliability horizontal ellipsis The usual procedure is to use discretization schemes which unfortunately introduce some error in the target distribution. Our aim is to present a new algorithm which simulates exactly the exit time for one-dimensional diffusions. This acceptance-rejection algorithm requires to simulate exactly the exit time of the Brownian motion on one side and the Brownian position at a given time, constrained not to have exit before, on the other side. Crucial tools in this study …

Gray code for permutations with a fixed number of cycles

2007

AbstractWe give the first Gray code for the set of n-length permutations with a given number of cycles. In this code, each permutation is transformed into its successor by a product with a cycle of length three, which is optimal. If we represent each permutation by its transposition array then the obtained list still remains a Gray code and this allows us to construct a constant amortized time (CAT) algorithm for generating these codes. Also, Gray code and generating algorithm for n-length permutations with fixed number of left-to-right minima are discussed.

Road Planning and Route Alignment Selection Criteria in the Norwegian Context

2019

This paper reveals the main factors that guide road alignment design process in Norway. The goal is to discover what constitutes the main priorities for road planners, how these priorities are ranked when it comes to alignment selection, and how they are related to guiding factors identified in official planning documents and government transport plans throughout the life cycle of a road. This is done through a comprehensive literature and data search, involving published academic research in the road alignment design field, and by exploring Norwegian road planning documents and guidelines. Examples from a recently implemented road project are also included as a way to illustrate alignment …

Semisupervised nonlinear feature extraction for image classification

2012

Feature extraction is of paramount importance for an accurate classification of remote sensing images. Techniques based on data transformations are widely used in this context. However, linear feature extraction algorithms, such as the principal component analysis and partial least squares, can address this problem in a suboptimal way because the data relations are often nonlinear. Kernel methods may alleviate this problem only when the structure of the data manifold is properly captured. However, this is difficult to achieve when small-size training sets are available. In these cases, exploiting the information contained in unlabeled samples together with the available training data can si…

Parallel Algorithms for Listing Well-Formed Parentheses Strings

1998

We present two cost-optimal parallel algorithms generating the set of all well-formed parentheses strings of length 2n with constant delay for each generated string. In our first algorithm we generate in lexicographic order well-formed parentheses strings represented by bitstrings, and in the second one we use the representation by weight sequences. In both cases the computational model is based on an architecture CREW PRAM, where each processor performs the same algorithm simultaneously on a different set of data. Different processors can access the shared memory at the same time to read different data in the same or different memory locations, but no two processors are allowed to write i…

Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosis

2011

In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning stops once this set has been processed. Training these classifiers requires a representative amount of data, but the gathering, preprocess, and validation of samples is expensive and time-consuming. Therefore, for a classical, non-incremental approach to ML, it is necessary to wait long enough to collect all the required data. In contrast, an incremental learning approach may allow us to build an initial classifier with a smaller number of samples and update it incrementally…

Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation

2018

Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…