A.S. Pyataev · Siberian Journal of Science and Technology · 2018
Nowadays tree modeling algorithms are used in different fields of activity: from computer games to the plantation forest management.Tree modeling algorithm parameters can depend on different factors: it could be features of landscape, climate or geographical location.Depending on the tasks to be solved, the detail level of the created model is chosen.Forest management tasks often do not require a high detail level, it is sufficient to construct a schematic plantation model.For computer games the creation of photorealistic models is required.The paper proposes an algorithm of 3D tree modeling which consists of the following steps: first step -building a tree framework (modeling the growth of a tree and adding new nodes), while under the framework is meant a set of three-dimensional vectors with attributive data for each vector; then building a tree and overlaying textures.The trunk and branches of the modeled tree are approximated by truncated cones, the axes of which are the vectors of the frame.The tree model constructing algorithm is iterative.Every iteration is a tree growth stage.Thus, the tree is gradually grown to the required level.The developed algorithm allows modeling trees of different state categories.The feature of the proposed algorithm is the possibility of constructing a three-dimensional tree model with any detail level.For example, for coniferous trees it is possible to built a tree up to each needle.
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Narcis Fern, Baldomero Oliva, András Fiser · 2006
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Oliveira, Nuno André Lapa · The Scientific Repository of the Polytechnic Institute of Porto (Polytechnic Institute of Porto) · 2022
As of today, the most recent trend in information technology is the employment of large-scale data analytic methods powered by Artificial Intelligence (AI), influencing the priorities of businesses and research centers all over the world. However, due to both the lack of specialized talent and the need for greater compute, less established businesses struggle to adopt such endeavors, with major technological mega-corporations such as Microsoft, Facebook and Google taking the upper hand in this uneven playing field. Therefore, in an attempt to promote the democratization of AI and increase the efficiency of data scientists, this work proposes a novel no-code/low-code AI platform: the ALgorithm Modeling Application (ALMA). Moreover, as the state of the art of such platforms is still gradually maturing, current solutions often fail into encompassing security/safety aspects directly into their process. In that respect, the solution proposed in this thesis aims not only to achieve greater development and deployment efficiency while building machine learning applications but also to build upon others by addressing the inherent pitfalls of AI through a ”secure by design” philosophy.
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Matthew L. Rizk (370774), James C. Liao (184646) · Figshare · 2015
<p>The algorithm is illustrated on the left, while the steps are described in detail on the right.</p>
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Simone Grassi, Stephen Barrett, Francesco Sordillo · 2007
Our work addresses the issue of software adaptation in Service Oriented Architecture (SOA) environments. We aim to support a wide range of adaptations using a new formulation of Web Service (WS) model based on client driven service adaptation via ontological description of algorithms. We describe how this approach can be applied to a SOA scenario involving heterogeneous systems, and report on experimental work that demonstrates how services can be transformed in practice, using a framework approach.
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Jianying Zhang · 2008
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Mastorakis, Nikos E · CERN Document Server (European Organization for Nuclear Research) · 2011
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2012
We derive the Expectize-Maximize algorithm (EM) for Gaussian Mixture modeling (GMM). In general, any random space can be modeled by a mixture (weighed linear combination) of normal densities. Then, such an arbitrary density can be represented as: where f(φ; y) = K∑ λkfk(θk; y) (1) k=1 • K is the total number of densities • y is the data vector • φ = [λ1... λK, θ1... θK] and θk = [µ k, Σk] represent the mean vector and covariance matrix of the kth density • fk ∼ N (µ k, Σk) • {λk} represent the mixing weights with constraint ∑ K k=1 λk = 1 From now onwards, we drop the bold face notation for vectors and matrices for convenience. To derive the EM algorithm, we need to identify the missing information. Often identifying this missing information can lead to different results affecting convergence. In the mixture modeling problem, if know the label of the data, i.e., if we know the density index that could have possibly produced the observation, we could easily estimate the mixture parameters by simply collecting all the data corresponding to that particular density. In other words, if we associate each observation to one of the K densities, estimating each density parameters is trivial. Hence, we choose the label as the missing information. Once we identify the missing information, we need to define the complete data likelihood and marginal unobserved data density conditional on the observed data. A very good explanation of the EM algorithm is given in[1, pp.66-87] Let u(n) ∈ {1... K} be the missing label corresponding to the nth observation y(n). The marginal density (in fact pmf) of this unobserved data is then given as: p(u(n) = k) = λk (2) The density of the observed data given the unobserved data is: p(y(n)|u(n)) = f u(n)(y(n); θ u(n)) (3) Then we obtain the complete data density as: p(y(n), u(n); φ) = f u(n)(y(n); θ u(n))λ u(n) (4) www.asankhya.org/me
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Dong‐Ming Yan, Hui Zhang, Jun‐Hai Yong et al. · Lecture notes in computer science · 2004
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Ompal Singh, Satish Kumar, Shakeeluddin Chaudhary · 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM) · 2022
This paper presented two major reasons that may decide to move service unit. The first reason is related with possible change in arrangement topology. When we determine the link length in the unit of travel time, it often happens travel time is varies between two nodes. Cost reflection plays the major role in decision making. Dispatch center having no real time communication capacity with moving unit. It is not easy communicate with moving unit, when it is in roaming. We talk about a model with possible link length. We developed the model under location as well as analysis problem.
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Chi Wan Lim (553836), Yi Su (311753), Si Yong Yeo (553837) et al. · Figshare · 2015
<p>Using the segmented contours from the first time step, we go through each adjacent pairs of contours and establish the intra-connectivities between them. Using these connections, we reconstruct a 3D mesh model and set it as the generated mesh model of the first time step. For each subsequent time step, the segmented contours are passed through the tree-based connectivity process to establish their inter- and intra-connectivities. They are then compared with the mesh model from the current time step in a sub-mesh by sub-mesh manner. If there is no 1-to-1 contour correspondence, they are then passed through the 2D topological change process before performing the 1-to-1 contour matching process. Finally, the mesh model of the current time step is generated when the mesh is fully deformed.</p>
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Attilio Immirzi (2469385) · Figshare · 2016
A molecular modeling procedure, based on internal coordinates and strictly analytical even in the most\nintricated cases, is described. Internal coordinates, always nonredundant, become mutually independent and\ncan be varied without constraints. Structural refinement from diffraction data (Least-square method, LS)\ncan be done using the classical Gauss−Newton approach and avoiding Lagrange multipliers. A comparative\ntest done using published data has shown that while the new method gives rise to a structural refinement in\nperfect agreement with the known structure, the traditional methods (<b>z</b>-matrix and constraints based) does\nnot work.
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Karen M. Madsen, A. Elizabeth Perry · Scholarworks (University of Massachusetts Amherst) · 2024
This paper presents a practical application for writing and applying simple genetic algorithms (GAs) for the common groundwater flow model, MODFLOW. The method employed by GAs is derived from the driving forces of evolution in the natural world. They employ functions that mimic natural evolutionary processes including selection, mutation, and genetic crossover. A GA solves mathematical problems where a desired outcome to the problem is defined (for example, calibration targets or remediation goals), but the inputs needed to arrive at this outcome are unknown. Our paper includes an introduction to genetic algorithms, the pseudocode of our genetic algorithm for MODFLOW, and the results of an experiential application. Due to the lack of commercially available GAs for MODFLOW, we coded a simple algorithm in Visual Basic Script and applied it to an example model. In the example model, the GA was used to conduct parameter estimation on a MODFLOW model of a river basin in New England that we had previously developed and calibrated in our practice. The calibration target used was net groundwater flow into the river. Four model input parameters were selected as chromosomes for the GA to act on: recharge, river conductance, and two general head boundaries. An initial population of 100 models was developed by varying the value of the gene parameters. The GA ran a MODFLOW simulation for each member of the population, extracted each output file, and established the error of each model from the calibration target. It then evolved the entire population of models towards the calibration target. The GA converged on a single set of input parameter that established best-fit values for all of the chromosome parameters. Genetic algorithms provide a practical alternative to trial-and-error and automated statistical calibration procedures, and can also be used for optimization.
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2014
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Amir Sharif Ahmadian · Elsevier eBooks · 2016
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Jianhong Ma · 2013
The paper proposed a nonlinear sensor dynamic modeling algorithm for the r dynamic of Sensor.The parameters of LSSVM model were considered the position vector of ants while the accuracy of sensor dynamic model was taken as the object function,and then target individuals were determined by dynamic and stochastic extraction which make ants search global rapidly,and carried out small step search for the optimal ant of this generation.Lastly,the optimal parameter value was obtained by ACO,and the sensor dynamic model was built.The results show that the proposed method is reliable and practicable,and it creates favorable conditions for proving dynamic performance and online compensation of the sensors.
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Yuldashov Shavkat Nuriddin o'g'li · Zenodo (CERN European Organization for Nuclear Research) · 2024
This paper succinctly illustrates challenges encountered when modelling systems mathematically. Mathematical modelling entirely entails math symbols, numbers and relations forming a functional equation. These mathematical equations can represent any system of interests, also provides ease computer simulations. Mathematical models are extensively utilized in different fields i.e. engineering, by scientists, and analysts to give a clear understanding of the problem. Modelling contributed a lot since inversion of the concept. Simple and complex structures erected as a result of modelling. In that sense modelling is an important part of engineering. It can be referred to as the primary building block of every system. A complex model however is not an ideal solution. Engineers have to be cautious not to discard all information as this might render the designed model useless – as detailed in this paper the model should be simple with all necessary and relevant data. Basically the purpose of this paper is to show the importance and clearly explain in detail challenges encountered when modelling.
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Shanying Cheng · 2012
In order to improve the precision of the control system and reduce the sensor modeling errors,this paper proposed an improved sensor dynamic modeling algorithm.The improved support vector machine was used for the sensor dynamic modeling,which reflects the dynamic characteristics.The chaotic particle swarm algorithm was used to optimize the parameters of the model to improve the control precision.The simulation results show that the method can quickly find the optimal parameters and improve the accuracy of the control system.The model is of good practicality and provides a new method for sensor dynamic modeling.
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Attilio Immirzi (2469385) · Figshare · 2016
A molecular modeling procedure, based on internal coordinates and strictly analytical even in the most\nintricated cases, is described. Internal coordinates, always nonredundant, become mutually independent and\ncan be varied without constraints. Structural refinement from diffraction data (Least-square method, LS)\ncan be done using the classical Gauss−Newton approach and avoiding Lagrange multipliers. A comparative\ntest done using published data has shown that while the new method gives rise to a structural refinement in\nperfect agreement with the known structure, the traditional methods (<b>z</b>-matrix and constraints based) does\nnot work.
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Larisa Bulysheva, Alexander Bulyshev · Information Technology and Management · 2012
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