Relevant bibliographies by topics / Linjär algoritm

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Linjär algoritm'

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Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Linjär algoritm"

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Cáceres, José, and Alberto Márquez. "A linear algorithm to recognize maximal generalized outerplanar graphs." Mathematica Bohemica 122, no. 3 (1997): 225–30. http://dx.doi.org/10.21136/mb.1997.126148.

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Amrullah, Muhammad. "PEMODELAN PEMROGRAMAN LINIER DENGAN KOEFISIEN FUNGSI OBJEKTIF, FUNGSI KENDALA DAN VARIABEL KEPUTUSAN BERBENTUK BILANGAN KABUR BESERTA APLIKASINYA." Jurnal Matematika, Statistika dan Komputasi 16, no. 1 (June 27, 2019): 85. http://dx.doi.org/10.20956/jmsk.v16i1.5802.

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Abstrak Dalam penelitian ini penulis akan mengusulkan algoritma untuk memodelkan masalah pemrograman linear kabur dengan bilangan kabur trapesium menggunakan metode simpleks. Secara khusus dalam aplikasi teori ini adalah masalah pengambilan keputusan pemrograman linear kabur dengan menyajikan metode baru untuk menyelesaikan masalah pemrograman linier kabur dengan menggunakan fungsi ranking. Pada dasarnya, langkah-langkah dalam metode penelitian ini sama dengan dengan metode simpleks yang digunakan untuk memecahkan masalah pemrograman linier tegas.Kata kunci: Fuzzy linear programming, fungsi ranking, metode simpleks. AbstractIn this paper author shall propose an algorithm for solving fuzzy linear programming problems with trapezoidal numbers using a simplex method. In particular, an application of this theory in decision making problems is fuzzy linear programming with a new method for solving fuzzy linear programming problems, by use of rank function. Basically, our method is similar to simplex method that was used for solving linear programming problems in crisp environment before.Keywords: Fuzzy linier programming, rank function, simplex method.
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Patel, Roshni V., and Jignesh S. Patel. "Optimization of Linear Equations using Genetic Algorithms." Indian Journal of Applied Research 2, no. 3 (October 1, 2011): 56–58. http://dx.doi.org/10.15373/2249555x/dec2012/19.

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PAȘA, Tatiana. "THE GENETIC ALGORITHM FOR SOLVING THE NON-LINEAR TRANSPORTATION PROBLEM." Review of the Air Force Academy 16, no. 2 (October 31, 2018): 37–44. http://dx.doi.org/10.19062/1842-9238.2018.16.2.4.

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Mahapatra, Gautam, Srijita Mahapatra, and Soumya Banerjee. "A Study of Firefly Algorithm and its Application in Non-Linear Dynamic Systems." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (February 28, 2018): 542–49. http://dx.doi.org/10.31142/ijtsrd8393.

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Sharma, Aditya, and Er Praveen Kumar Patidar. "Review on Linear Array Antenna with Minimum Side Lobe Level Using Genetic Algorithm." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 2067–70. http://dx.doi.org/10.31142/ijtsrd14544.

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Marusenkova, T. "A gating algorithm with reduced computational complexity for linear Kalman filters in embedded systems." Jornal of Kryvyi Rih National University, no. 50 (2020): 25–31. http://dx.doi.org/10.31721/2306-5451-2020-1-50-25-31.

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Han, F., X. Huang, E. Teye, H. Gu, H. Dai, and L. Yao. "A nondestructive method for fish freshness determination with electronic tongue combined with linear and non-linear multivariate algorithms." Czech Journal of Food Sciences 32, No. 6 (November 27, 2014): 532–37. http://dx.doi.org/10.17221/88/2014-cjfs.

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Electronic tongue coupled with linear and non-linear multivariate algorithms was attempted to address the drawbacks of fish freshness detection. Parabramis pekinensis fish samples stored at 4&deg;C were used. Total volatile basic nitrogen (TVB-N) and total viable count (TVC) of the samples were measured. Fisher liner discriminant analysis (Fisher LDA) and support vector machine (SVM) were applied comparatively to classify the samples stored at different days. The results revealed that SVM model was better than Fisher LDA model with a higher identification rate of 97.22% in the prediction set. Partial least square (PLS) and support vector regression (SVR) were applied comparatively to predict the TVB-N and TVC values. The quantitative models were evaluated by the root mean square error of prediction (RMSEP) and the correlation coefficient in the prediction set (R<sub>pre</sub>). The results revealed that SVR model was superior to PLS model with RMSEP = 5.65 mg/100 g, R<sub>pre</sub> = 0.9491 for TVB-N prediction and RMSEP = 0.73 log CFU/g, R<sub>pre</sub>&nbsp;= 0.904 for TVC prediction. This study demonstrated that the electronic tongue together with SVM and SVR has a great potential for a convenient and nondestructive detection of fish freshness. &nbsp;
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Gusti, Kharisma Wiati, Rinda Cahyana, and Luthfi Nurwandi. "Simulasi Perhitungan Integral Non Linier Menggunakan Monte Carlo (Studi Kasus Ekonomi Total Biaya)." Jurnal Algoritma 9, no. 2 (September 1, 2012): 406–15. http://dx.doi.org/10.33364/algoritma/v.9-2.406.

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Mukesh, Anand Mohan Sinha, Kumar. "Algorithm for Linear Programming." IOSR Journal of Mathematics 4, no. 4 (2012): 48–51. http://dx.doi.org/10.9790/5728-0444851.

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Dissertations / Theses on the topic "Linjär algoritm"

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Åkerling, Erik, and Jimmy Jerenfelt. "Analys och framtagning av algoritm för rodermätning." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-23459.

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Arbetet är ett utredningsarbete som går ut på att försöka lokalisera felkällor och göra förbättringar på en testutrustning som mäter rodervinklar på akterdelen på en robot. Rapporten innehåller en översiktlig bild över den tidigare metoden och dess felkällor som hittas vid test av den tidigare metoden. Utredningen utmanar också många utav antagandena som är gjorda för beräkningarna av den tidigare metoden. Detta utförs för att kunna bekräfta eller dementera antagandena. Detta görs i form av matematiska modeller som testar olika delar av metoden. Varje del i rapporten består av en beskrivning av vad kapitlet avser följt av felkällorna som upptäckts i metoden när den testas i modellen. Det framtagna metodförslaget utsätts samma prövning som den tidigare metoden för att utreda skillnaderna. I resultatet kan man se de slutsatser som dragit av varje del av utförandet.
The task is an investigation to try and locate errors and make improvements on a test equipment that measures rudder angles on the rear-end of a robot. The report contains an overview of the previous method and the errors that is found by testing it. The investigation also challenges many of the assumptions made when the previous method was made. This was made in order to either confirm or deny the assumptions. This is done by the use of mathematical models to simulate different parts of the method. Each part of the report consists of a description of the section followed by explaining the discovered errors that was found by testing the method in the models. The new produced method suggestion is exposed to the same tests as the previous method to discern the differences. The conclusions made from the sections can be found in the results.
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Sehovic, Mirsad, and Markus Carlsson. "Nåbarhetstestning i en baneditor : En undersökning i hur nåbarhetstester kan implementeras i en baneditor samt funktionens potential i att ersätta manuell testning." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-36394.

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Denna studie undersöker om det är möjligt att införa nåbarhetstestning i en baneditor. Testets syfte är att ersätta manuell testing, det vill säga att bankonstruktören inte ska behöva spela igenom banan för att säkerställa att denne kommer kunna nå alla nåbara positioner.För att kunna utföra studien skapas en enkel baneditor som testplattform. Vidare utförs en jämförande studie av flera alternativa algoritmer för att fastställa vilken som är mest passande för nåbarhetstestning i en baneditor.Resultatet från den jämförande studien visade att A* (A star) var den mest passande algoritmen för funktionen. Huruvida automatisk testning kan ersätta manuell testning är diskutabelt, men resultatet pekar på en ökad effektivitet i tid när det kommer till banbygge.
The following study examines whether it is possible to implement reachability testing in a map editor designed for 2D-platform games. The purpose of reachability testing is to replace manual testing, that being the level designer having to play through the map just to see if the player can reach all supposedly reachable positions in the map.A simple map editor is created to enable the implementation after which we perform a theoretical study in order to determine which algorithm would be best suited for the implementation of the reachability testing.The results comparing algorithms shows that A* (A star) worked best with the function. Whether or not manual testing can be replaced by automatic testing is open for debate, however the results points to an increase in time efficiency when it comes to level design.
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Morad, Farhad. "Non-linear Curve Fitting." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-43600.

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The work done in this thesis is to examine various methods for curve fitting. Linear least squares and non-linear least squares will be described and compared, and the Newton method, Gauss--Newton method and Levenberg--Marquardt method will be applied to example problems.
Syftet med denna uppsats är att beskriva och använda olika metoder för kurvanpassning, det vill säga att passa matematiska funktioner till data. De metoder som undersöks är Newtons metod, Gauss--Newton metoden och Levenberg--Marquardt metoden. Även skillnaden mellan linjär minsta kvadrat anpassning och olinjär minsta kvadrat anpassning. Till sist tillämpas Newton, Gauss Newton och Levenberg--Marquardt metoderna på olika exempel.
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Uyanga, Enkhzul, and Lida Wang. "Algorithm that creates productcombinations based on customerdata analysis : An approach with Generalized Linear Modelsand Conditional Probabilities." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210176.

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This bachelor’s thesis is a combined study of applied mathematical statistics and industrial engineering and management implemented to develop an algorithm which creates product combinations based on customer data analysis for eleven AB. Mathematically, generalized linear modelling, combinatorics and conditional probabilities were applied to create sales prediction models, generate potential combinations and calculate the conditional probabilities of the combinations getting purchased. SWOT analysis was used to identify which factors can enhance the sales from an industrial engineering and management perspective. Based on the regression analysis, the study showed that the considered variables, which were sales prices, brands, ratings, purchase countries, purchase months and how new the products are, affected the sales amounts of the products. The algorithm takes a barcode of a product as an input and checks whether if the corresponding product type satisfies the requirements of predicted sales amount and conditional probability. The algorithm then returns a list of possible product combinations that fulfil the recommendations.
Detta kandidatexamensarbete är en kombinerad studie av tillämpad matematisk statistik och industriell ekonomisk implementering för att utveckla en algoritm som skapar produktkombinationer baserad på kunddata analys för eleven AB. I den matematiska delen tillämpades generaliserade linjära modeller, kombinatorik och betingade sannolikheter för att skapa prediktionsmodeller för försäljningsantal, generera potentiella kombinationer och beräkna betingade sannolikheter att kombinationerna bli köpta. SWOT-analys användes för att identifiera vilka faktorer som kan öka försäljningen från ett industriell ekonomiskt perspektiv. Baserat på regressionsanalysen, studien har visat att de betraktade variablerna, som var försäljningspriser, varumärken, försäljningsländer, försäljningsmånader och hur nya produkterna är, påverkade försäljningsantalen på produkterna. Algoritmen tar emot en streckkod av en produkt som inmatning och kontrollerar om den motsvarande produkttypen uppfyller kraven för predikterad försäljningssumma och betingad sannolikhet. Algoritmen returnerar en lista av alla möjliga kombinationer på produkter som uppfyller rekommendationerna.
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Silva, Jair da. "Uma familia de algoritmos para programação linear baseada no algoritmo de Von Neumann." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306741.

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Orientador: Aurelio R. Leite Oliveira, Marta Ines Velazco
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: Neste trabalho apresentamos uma nova família de algoritmos para resolver problemas de programação linear. A vantagem desta família de algoritmos é a sua simplicidade, a possibilidade de explorar a esparsidade dos dados do problema original e geralmente possuir raio de convergência inicial rápido. Esta família de algoritmos surgiu da generalização da idéia apresentada por João Gonçalves, Robert Storer e Jacek Gondzio, para desenvolver o algoritmo de ajustamento pelo par ótimo. Este algoritmo foi desenvolvido por sua vez tendo como base o algoritmo de Von Neumann. O algoritmo de Von Neumann possui propriedades interessantes, como simplicidade e convergência inicial rápida, porém, ele não é muito prático para resolver problemas lineares, visto que sua convergência é muito lenta. Do ponto de vista computacional, nossa proposta não é utilizar a família de algoritmos para resolver os problemas de programação linear até encontrar uma solução e sim explorar a sua simplicidade e seu raio de convergência inicial geralmente rápido e usá-la em conjunto com um método primal-dual de pontos interiores infactível, para melhorar a eficiência deste. Experimentos numéricos revelam que ao usar esta família de algoritmos em conjunto com um método primal-dual de pontos interiores infactível melhoramos o seu desempenho na solução de algumas classes de problemas de programação linear de grande porte.
Abstract: In this work, we present a new family of algorithms to solve linear programming problems. The advantage of this family of algorithms relies in its simplicity, the possibility of exploiting the sparsity of the original problem data and usually to have fast initial ratio of convergence. This family of algorithms arose from the generalization of the idea presented by João Gonçalves, Robert Storer and Jacek Gondzio to develop the optimal pair adjustment algorithm. This algorithm was developed in its own turn based on the Von Neumann's algorithm. It has interesting properties, such as simplicity and fast initial convergence, but it is not very practical for solving linear problems, since its convergence is very slow. From the computational point of view, our suggestion is not to use the family of algorithms to solve problems of linear programming until optimality, but to exploit its simplicity and its fast initial ratio of convergence and use it together with a infeasible primal-dual interior point method to improve its efficiency. Numerical experiments show that using this family of algorithms with an infeasible primal-dual interior point method improves its performance in the solution of some classes of large-scale linear programming problems.
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Wilbanks, John W. (John Winston). "Linear Unification." Thesis, University of North Texas, 1989. https://digital.library.unt.edu/ark:/67531/metadc500971/.

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Efficient unification is considered within the context of logic programming. Unification is explained in terms of equivalence classes made up of terms, where there is a constraint that no equivalence class may contain more than one function term. It is demonstrated that several well-known "efficient" but nonlinear unification algorithms continually maintain the said constraint as a consequence of their choice of data structure for representing equivalence classes. The linearity of the Paterson-Wegman unification algorithm is shown largely to be a consequence of its use of unbounded lists of pointers for representing equivalences between terms, which allows it to avoid the nonlinearity of "union-find".
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Lammoglia, Bruna. "Sobre minimização de quadraticas em caixas." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306045.

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Orientador: Maria Aparecida Diniz Ehrhardt
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: Neste trabalho o objetivo principal foi a minimização de quadráticas em caixas. Dissertamos sobre os métodos de máxima descida e dos gradientes conjugados, bem como sobre um método mais recente denominado gradiente espectral. O GENCAN, um algoritmo que minimiza funções em caixas, foi estudado em detalhe, particularmente avaliando sua aplicação para quadráticas. O objetivo foi analisar o desempenho do GENCAN, comparado com algoritmos anteriores, como o LANCELOT e o QUACAN. Foram executados experimentos numéricos a fim de avaliar o desempenho das versões de GENCAN sem e com pré-condicionamento. Concluiu-se que pré-condicionar o método dos gradientes conjugados neste caso tornou o GENCAN mais robusto. No entanto, o pré-condicionador usado neste software mostrou-se computacionalmente caro. Em relação à comparação do GENCAN, LANCELOT e QUACÁN, podemos afirmar que o GENCAN. mostrou-se competitivo
Abstract: The focus of this work was the minimization of quadratic functions with box constraints. We were mainly concerned about the steepest descent and conjugated gradient methods, besides a more recent approach called spectral gradient method. The GENCAN, an algorithm that minimizes functions on a box, was studied in details particularly evaluating this algorithm applied to quadratics. The objective was to analyze the efficiency of GENCAN, comparing it to classical algorithms, such as LANCELOT and QUACAN. We executed numerical experiments in order to investigate the efficiency of GENCAN version with and without preconditioning. Evaluating the results we concluded that preconditioning the conjugated gradient method makes the GENCAN work considerably better; despite the fact that the preconditioner used here turned the computational process more expensive. Comparing GENCA'N, LANCELOT, and QUACAN we can state that GENCAN is competitive
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Mestre em Matemática Aplicada
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Paula, Lauro Cássio Martins de. "Paralelização de algoritmos APS e Firefly para seleção de variáveis em problemas de calibração multivariada." Universidade Federal de Goiás, 2014. http://repositorio.bc.ufg.br/tede/handle/tede/3418.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
The problem of variable selection is the selection of attributes for a given sample that best contribute to the prediction of the property of interest. Traditional algorithms as Successive Projections Algorithm (APS) have been quite used for variable selection in multivariate calibration problems. Among the bio-inspired algorithms, we note that the Firefly Algorithm (AF) is a newly proposed method with potential application in several real world problems such as variable selection problem. The main drawback of these tasks lies in them computation burden, as they grow with the number of variables available. The recent improvements of Graphics Processing Units (GPU) provides to the algorithms a powerful processing platform. Thus, the use of GPUs often becomes necessary to reduce the computation time of the algorithms. In this context, this work proposes a GPU-based AF (AF-RLM) for variable selection using multiple linear regression models (RLM). Furthermore, we present two APS implementations, one using RLM (APSRLM) and the other sequential regressions (APS-RS). Such implementations are aimed at improving the computational efficiency of the algorithms. The advantages of the parallel implementations are demonstrated in an example involving a large number of variables. In such example, gains of speedup were obtained. Additionally we perform a comparison of AF-RLM with APS-RLM and APS-RS. Based on the results obtained we show that the AF-RLM may be a relevant contribution for the variable selection problem.
O problema de seleção de variáveis consiste na seleção de atributos de uma determinada amostra que melhor contribuem para a predição da propriedade de interesse. O Algoritmo das Projeções Sucessivas (APS) tem sido bastante utilizado para seleção de variáveis em problemas de calibração multivariada. Entre os algoritmos bioinspirados, nota-se que o Algoritmo Fire f ly (AF) é um novo método proposto com potencial de aplicação em vários problemas do mundo real, tais como problemas de seleção de variáveis. A principal desvantagem desses dois algoritmos encontra-se em suas cargas computacionais, conforme seu tamanho aumenta com o número de variáveis. Os avanços recentes das Graphics Processing Units (GPUs) têm fornecido para os algoritmos uma poderosa plataforma de processamento e, com isso, sua utilização torna-se muitas vezes indispensável para a redução do tempo computacional. Nesse contexto, este trabalho propõe uma implementação paralela em GPU de um AF (AF-RLM) para seleção de variáveis usando modelos de Regressão Linear Múltipla (RLM). Além disso, apresenta-se duas implementações do APS, uma utilizando RLM (APS-RLM) e uma outra que utiliza a estratégia de Regressões Sequenciais (APS-RS). Tais implementações visam melhorar a eficiência computacional dos algoritmos. As vantagens das implementações paralelas são demonstradas em um exemplo envolvendo um número relativamente grande de variáveis. Em tal exemplo, ganhos de speedup foram obtidos. Adicionalmente, realiza-se uma comparação do AF-RLM com o APS-RLM e APS-RS. Com base nos resultados obtidos, mostra-se que o AF-RLM pode ser uma contribuição relevante para o problema de seleção de variáveis.
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Dal, Gallo Rodrigo Marchiori. "Metodo heuristico eficiente para problemas de programação linear inteira com dimensão completa." [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306197.

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Orientador: Antonio Carlos Moretti
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: O trabalho tem como objetivo a implementação de um método heurístico para a resolução de problemas de programação inteira com dimensão completa. Nos atemos aos problemas de corte e empacotamento, mas a aplicação pode ser estendida a qualquer outro problema dessa classe. No problema de programação linear relaxado aplicamos o Método de Gilmore & Gomory e a partir da solução contínua obtida através do método simplex, aplicamos o método heurístico e comparamos os resultados com as soluções exatas obtidas a partir de Branch & Bound
Abstract: The objective of this dissertation is the implementation of a heuristic method to solve integer linear programming problems with complete dimension. We worked specifically with cutting and stock problems, but it can be aplied to any other class of integer problems. We used the Gilmore & Gomory method of column generation and starting by the continuous solution obtained with simplex method, we aplied the heuristic method and made a comparation of results with the exact solutions obtained by the Branch&Bound method
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Pesquisa Operacional
Mestre em Matemática Aplicada
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Chee, Sonny Han Seng. "RecTree, a linear collaborative filtering algorithm." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0011/MQ61420.pdf.

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Books on the topic "Linjär algoritm"

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Currie, James D. The complexity of the simplex algorithm. [Ottawa]: Carleton University, Mathematics and Statistics, 1985.

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Sima, Vasile. Algorithms for linear-quadratic optimization. New York: M. Dekker, 1996.

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Mathematical algorithms for linear regression. Boston: Academic Press, 1991.

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Kontoghiorghes, Erricos John. Parallel Algorithms for Linear Models. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4571-2.

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Lee, P. Synthesizing linear-array algorithms from nested for loop algorithms. New York: Courant Institute of Mathematical Sciences, New York University, 1988.

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I, Agoshkov V., and Shuti͡a︡ev V. P, eds. Sopri͡a︡zhennye uravnenii͡a︡ i algoritmy vozmushcheniĭ. Moskva: Akademii͡a︡ nauk SSSR, Otdel vychislitelʹnoĭ matematiki, 1986.

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Panik, Michael J. Linear programming: Mathematics, theory and algorithms. Dordrecht: Kluwer Academic, 1996.

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Abdullah, Jalaluddin. Fixed point algorithms for linear programming. Birmingham: University of Birmingham, 1992.

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service), SpringerLink (Online, ed. Max-linear Systems: Theory and Algorithms. London: Springer-Verlag London Limited, 2010.

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Linear network optimization: Algorithms and codes. Cambridge, Mass: MIT Press, 1991.

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Book chapters on the topic "Linjär algoritm"

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Karloff, Howard. "Karmarkar’s Algorithm." In Linear Programming, 103–30. Boston, MA: Birkhäuser Boston, 2009. http://dx.doi.org/10.1007/978-0-8176-4844-2_5.

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Karloff, Howard. "The Ellipsoid Algorithm." In Linear Programming, 73–101. Boston, MA: Birkhäuser Boston, 2009. http://dx.doi.org/10.1007/978-0-8176-4844-2_4.

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Karloff, Howard. "The Simplex Algorithm." In Linear Programming, 23–47. Boston, MA: Birkhäuser Boston, 2009. http://dx.doi.org/10.1007/978-0-8176-4844-2_2.

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Kall, Peter, and János Mayer. "Algorithms." In Stochastic Linear Programming, 285–382. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7729-8_4.

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Bitan, Sara, and Shmuel Zaks. "Optimal linear broadcast." In Algorithms, 368–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_86.

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Walrand, Jean. "Speech Recognition: B." In Probability in Electrical Engineering and Computer Science, 217–42. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_12.

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AbstractOnline learning algorithms update their estimates as additional observations are made. Section 12.1 explains a simple example: online linear regression. The stochastic gradient projection algorithm is a general technique to update estimates based on additional observations; it is widely used in machine learning. Section 12.2 presents the theory behind that algorithm. When analyzing large amounts of data, one faces the problems of identifying the most relevant data and of how to use efficiently the available data. Section 12.3 explains three examples of how these questions are addressed: the LASSO algorithm, compressed sensing, and the matrix completion problem. Section 12.4 discusses deep neural networks for which the stochastic gradient projection algorithm is easy to implement.
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Cottle, Richard W., and Mukund N. Thapa. "THE SIMPLEX ALGORITHM." In Linear and Nonlinear Optimization, 61–84. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7055-1_3.

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Korte, Bernhard, and Jens Vygen. "Linear Programming." In Algorithms and Combinatorics, 53–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56039-6_3.

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Rival, Ivan. "Linear Extensions." In Algorithms and Order, 481–82. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2639-4_17.

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Korte, Bernhard, and Jens Vygen. "Linear Programming." In Algorithms and Combinatorics, 49–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-21708-5_3.

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Conference papers on the topic "Linjär algoritm"

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Mulkay, Eric L., and Singiresu S. Rao. "Fuzzy Heuristics for Sequential Linear Programming." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/dac-3966.

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Abstract Numerical implementations of optimization algorithms often use parameters whose values are not strictly determined by the derivation of the algorithm, but must fall in some appropriate range of values. This work describes how fuzzy logic can be used to “control” such parameters to improve algorithms performance. This concept is shown with the use of sequential linear programming (SLP) due to its simplicity in implementation. The algorithm presented in this paper implements heuristics to improve the behavior of SLP based on current iterate values of design constraints and changes in search direction. Fuzzy logic is used to implement the heuristics in a form similar to what a human observer would do. An efficient algorithm, known as the infeasible primal-dual path-following interior-point method, is used for solving the sequence of LP problems. Four numerical examples are presented to show that the proposed SLP algorithm consistently performs better than the standard SLP algorithm.
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Graf, Norman A. "Clustering algorithm studies." In Physics and experiments with future linear e+ e- colliders. AIP, 2001. http://dx.doi.org/10.1063/1.1394455.

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Benke, M., E. Shapiro, and D. Drikakis. "FALCO: Fast Linear Corrector for Modelling DNA-Laden Flows." In ASME 2008 6th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2008. http://dx.doi.org/10.1115/icnmm2008-62131.

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The paper concerns the development of a numerical algorithm for improving the efficiency of computational fluid dynamics simulations of transport of biomolecules in microchannels at low number densities. For this problem, the continuum approach based on the concentration field model becomes invalid, whereas time scales involved make purely molecular simulations prohibitively computationally expensive. In this context, meta-models based on coupled solution of fluid flow equations and equations of motion for a simplified mechanical model of biomolecules provide a viable alternative. Meta-models often rely on particle-corrector algorithms, which impose length constraints on the mechanical DNA model. Particle-corrector algorithms are not sufficiently robust, thus resulting in slow convergence. A new geometrical particle corrector algorithm — called FALCO — is proposed in this paper, which significantly improves computational efficiency in comparison with the widely used SHAKE algorithm. It is shown that the new corrector can be related to the SHAKE algorithm by an appropriate choice of Lagrangian multipliers. Validation of the new particle corrector against a simple analytic solution is performed and the improved convergence is demonstrated for a macromolecule motion in a micro-cavity. This work has been supported in part by the European Commission under the 6th Framework Program (Project: DINAMICS, NMP4-CT-2007-026804).
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Hamann, Hendrik F. "Optimization Algorithms for Energy-Efficient Data Centers." In ASME 2013 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/ipack2013-73066.

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Real-time optimization algorithms for managing energy efficiency in data centers have been developed and implemented. For example, for a given cooling configuration (which is being measured and modeled in real-time using IBM’s Measurement and Management Technologies) an optimization algorithm allows identifying the optimum placement of new servers (or workloads) or alternatively where to remove servers (or workload) for different constraints. Another optimization algorithm optimizes performance of the data center without creating hotspots. The optimization algorithms use a physical model in junction with linear programming as well as linear least square methods.
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Van der Velden, Alex, and David Kokan. "The Synaps Pointer Optimization Engine." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34403.

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This paper describes a innovative optimization algorithm called Pointer. The Pointer software consists of a complementary set of optimization algorithms: linear simplex, sequential quadratic programming (SQP), downhill simplex, and genetic algorithms. Pointer can efficiently solve a wide range of problems in a fully automatic manner due to a special automatic control algorithm. The goal of the Pointer software is to make optimization more accessible to non-expert users without sacrificing performance.
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Ge, Cunjing, and Armin Biere. "Decomposition Strategies to Count Integer Solutions over Linear Constraints." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/192.

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Counting integer solutions of linear constraints has found interesting applications in various fields. It is equivalent to the problem of counting integer points inside a polytope. However, state-of-the-art algorithms for this problem become too slow for even a modest number of variables. In this paper, we propose new decomposition techniques which target both the elimination of variables as well as inequalities using structural properties of counting problems. Experiments on extensive benchmarks show that our algorithm improves the performance of state-of-the-art counting algorithms, while the overhead is usually negligible compared to the running time of integer counting.
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Lo, Chihsiung, and Panos Y. Papalambros. "A Convex Cutting Plane Algorithm for Global Solution of Generalized Polynomial Optimal Design Models." In ASME 1992 Design Technical Conferences. American Society of Mechanical Engineers, 1992. http://dx.doi.org/10.1115/detc1992-0121.

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Abstract Global optimization algorithms for generalized polynomial design models using a global feasible search approach was discussed in a previous article. A new convex cutting plane algorithm (CONCUT) based on global feasible search and with improved performance is presented in this sequel article. Computational results of the CONCUT algorithm compared to one using linear cuts (LINCUT) are given for various test problems. Two design examples, a speed reducer and a corrugated bulkhead design, illustrate the application of the algorithms.
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Ou, Mingdong, Nan Li, Shenghuo Zhu, and Rong Jin. "Multinomial Logit Bandit with Linear Utility Functions." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/361.

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Multinomial logit bandit is a sequential subset selection problem which arises in many applications. In each round, the player selects a K-cardinality subset from N candidate items, and receives a reward which is governed by a multinomial logit (MNL) choice model considering both item utility and substitution property among items. The player's objective is to dynamically learn the parameters of MNL model and maximize cumulative reward over a finite horizon T. This problem faces the exploration-exploitation dilemma, and the involved combinatorial nature makes it non-trivial. In recent years, there have developed some algorithms by exploiting specific characteristics of the MNL model, but all of them estimate the parameters of MNL model separately and incur a regret bound which is not preferred for large candidate set size N. In this paper, we consider the linear utility MNL choice model whose item utilities are represented as linear functions of d-dimension item features, and propose an algorithm, titled LUMB, to exploit the underlying structure. It is proven that the proposed algorithm achieves regret which is free of candidate set size. Experiments show the superiority of the proposed algorithm.
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Fine, Benjamin T., Hoday Stearns, and Masayoshi Tomizuka. "Identification in Iterative Learning Control: A Model Based, Iteration Varying Learning Filter for Precision Control." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2726.

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Linear Iterative Learning Control (ILC) algorithms have been known to also perform well for nonlinear systems whose dominant system dynamics are linear. In order for the learning filter to take advantage of more system information, we propose here a model based ILC algorithm which uses an iteration varying learning filter. Before the next iteration’s feedforward control is computed, the linearized system model is first estimated using a least squares approximation. We implement this algorithm on a wafer stage prototype whose dominant system dynamics are linear with a weak nonlinear actuator disturbance. Because the nonlinear disturbance is state dependent, the linear dynamics will shift as the ILC algorithm is converging. We show that as the system converges to the desired trajectory the plant parameter also converge.
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Nieto, Zackery, V. M. Krushnarao Kotteda, Arturo Rodriguez, Sanjay Shantha Kumar, Vinod Kumar, and Arturo Bronson. "Utilization of Machine Learning to Predict the Surface Tension of Metals and Alloys." In ASME 2018 5th Joint US-European Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fedsm2018-83248.

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As technology progresses, predictive solutions created by computer generated algorithms are becoming more and more viable. The purpose of this study is to test the predictive capabilities and their values of three different types of predictive algorithms, a multi-variable linear regression algorithm, a nonlinear random forest model, and a TensorFlow deep learning neural network model. To compare each algorithm, we used the surface tensions of the molten pure metals, copper, bismuth, and silver, as well as the copper-bismuth, and copper silver molten alloys. The surface tensions were then compiled into data sets meant for training and testing the algorithms predictive capabilities. Throughout this study, we considered how each algorithm could be corrected in ways to increase its predictability without over-constraining the algorithm to satisfy only these data sets. At the end, it became apparent that although the predictions of each algorithm were able to get to a fairly decent accuracy, the random forest model proved to be the best and most useful algorithm for surface tensions.
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Reports on the topic "Linjär algoritm"

1

Todd, Michael J., and Yinyu Ye. A Centered Projective Algorithm for Linear Programming. Fort Belvoir, VA: Defense Technical Information Center, February 1988. http://dx.doi.org/10.21236/ada192100.

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Entriken, Robert. A Parallel Decomposition Algorithm for Staircase Linear Programs. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada204662.

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Bixby, Robert E., and Donald K. Wagner. An Almost Linear-Time Algorithm for Graph Realization. Fort Belvoir, VA: Defense Technical Information Center, March 1985. http://dx.doi.org/10.21236/ada455177.

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Bernal, J. An expected linear 3-dimensional Voronoi diagram algorithm. Gaithersburg, MD: National Institute of Standards and Technology, 1990. http://dx.doi.org/10.6028/nist.ir.4340.

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Liang, Guanfeng, and Nitin Vaidya. Deterministic Consensus Algorithm with Linear Per-Bit Complexity. Fort Belvoir, VA: Defense Technical Information Center, August 2010. http://dx.doi.org/10.21236/ada555082.

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Forest, E. Normal form algorithm on non-linear symplectic maps. Office of Scientific and Technical Information (OSTI), April 1985. http://dx.doi.org/10.2172/6732425.

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Stechel, E. B. Linear scaling algorithms: Progress and promise. Office of Scientific and Technical Information (OSTI), August 1996. http://dx.doi.org/10.2172/285454.

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Tseng, Paul. A Very Simple Polynomial-Time Algorithm for Linear Programming. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada202502.

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Rokhlin, Vladimir, and Mark Tygert. A Fast Randomized Algorithm for Overdetermined Linear Least-Squares Regression. Fort Belvoir, VA: Defense Technical Information Center, April 2008. http://dx.doi.org/10.21236/ada489855.

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Saltzman, Robert M. A Heuristic Ceiling Point Algorithm for General Integer Linear Programming. Fort Belvoir, VA: Defense Technical Information Center, November 1988. http://dx.doi.org/10.21236/ada202285.

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