Relevant bibliographies by topics / Improved multi expression programming

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Improved multi expression programming'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Improved multi expression programming"

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Chen, Long Bin, and Pei He. "Multi-Subexpression Programming." Applied Mechanics and Materials 411-414 (September 2013): 2067–73. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2067.

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Gene Expression Programming is a new and adaptive brand evolution algorithm which is developed on the basis of genetic algorithm. In recent years, Multi-Expression Programming which is proposed in the genetic programming is a linear structure coding scheme,its main feature is a chromosome contains multiple expressions. The idea of MEP is introduced into the GEP in this paper, so a single GEP gene contains multiple solutions to solve the problem.The new algorithm analyzes each gene in the GEP to extract relational subexpressions, then fitness evaluate certain subexpressions to choose the best f
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Zhang, Qingke, Bo Yang, Lin Wang, and Jianzhang Jiang. "An improved multi-expression programming algorithm applied in function discovery and data prediction." International Journal of Information and Communication Technology 5, no. 3/4 (2013): 218. http://dx.doi.org/10.1504/ijict.2013.054952.

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Wang, Yu. "Study on Improved Flexible Neural Tree Optimization Algorithm." Advanced Materials Research 765-767 (September 2013): 1055–59. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1055.

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The BP neural network is easy to fall into local minimum point, the algorithm convergence speed slow, this paper puts forward an improved algorithm of flexible neural tree, introduced the basic theory knowledge of Flexible neural tree , analyzes the characteristics and advantages of the neural tree. The structure optimization and parameter optimization are adopted some optimization algorithm, Introduced the multi expression programming algorithm for optimization of flexible neural tree structure and by using the improved particle swarm algorithm to optimize the parameters of flexible neural tr
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Farajpanah, Hiwa, Morteza Lotfirad, Arash Adib, et al. "Ranking of hybrid wavelet-AI models by TOPSIS method for estimation of daily flow discharge." Water Supply 20, no. 8 (2020): 3156–71. http://dx.doi.org/10.2166/ws.2020.211.

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Abstract This research uses the multi-layer perceptron–artificial neural network (MLP-ANN), radial basis function–ANN (RBF-ANN), least square support vector machine (LSSVM), adaptive neuro-fuzzy inference system (ANFIS), M5 model tree (M5T), gene expression programming (GEP), genetic programming (GP) and Bayesian network (BN) with five types of mother wavelet functions (MWFs: coif4, db10, dmey, fk6 and sym7) and selects the best model by the TOPSIS method. The case study is the Navrood watershed in the north of Iran and the considered parameters are daily flow discharge, temperature and precip
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Giustolisi, O., and D. A. Savic. "Advances in data-driven analyses and modelling using EPR-MOGA." Journal of Hydroinformatics 11, no. 3-4 (2009): 225–36. http://dx.doi.org/10.2166/hydro.2009.017.

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Evolutionary Polynomial Regression (EPR) is a recently developed hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming/symbolic regression technique. The original version of EPR works with formulae based on true or pseudo-polynomial expressions using a single-objective genetic algorithm. Therefore, to obtain a set of formulae with a variable number of pseudo-polynomial coefficients, the sequential search is performed in the formulae space. This article presents an improved EPR strategy that uses a multi-objective g
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Chandra Sen. "Improved Weighted Sum Multi Objective Programming." January 2021 7, no. 01 (2021): 111–13. http://dx.doi.org/10.46501/ijmtst070126.

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Optimizing the combined objective function is the most common approach of Multi Objective Programming (MOP). The scalaization of objective functions have been recommended for combining the objective functions of various dimensions. The Weighted Sum Multi Objective Programming (WSMOP) has also been used for obtaining desirable solution. Several WSMOP methods are used for solving multi objective problems. Few weaknesses have noticed in WSMOP methods. An improved method of WSMOP is proposed in the present study for obtaining desirable solution of multi objective programming problems.
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Sharifi, Sohrab, Saeed Abrishami, and Amir H. Gandomi. "Consolidation assessment using Multi Expression Programming." Applied Soft Computing 86 (January 2020): 105842. http://dx.doi.org/10.1016/j.asoc.2019.105842.

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Al-Saati, Najla, and Taghreed Alreffaee. "Software Effort Estimation Using Multi Expression Programming." AL-Rafidain Journal of Computer Sciences and Mathematics 11, no. 2 (2014): 53–71. http://dx.doi.org/10.33899/csmj.2014.163756.

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Sheng, Zi Qiang. "Design Multi-Stage Draw by Improved Dynamic Programming." SAE International Journal of Materials and Manufacturing 3, no. 1 (2010): 716–22. http://dx.doi.org/10.4271/2010-01-0987.

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Ozlen, Melih, Benjamin A. Burton, and Cameron A. G. MacRae. "Multi-Objective Integer Programming: An Improved Recursive Algorithm." Journal of Optimization Theory and Applications 160, no. 2 (2013): 470–82. http://dx.doi.org/10.1007/s10957-013-0364-y.

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Dissertations / Theses on the topic "Improved multi expression programming"

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Mariano, Paulo Alexandre Lima da Silva. "RepComp - replicated software components for improved performance." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/5688.

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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática<br>The current trend of evolution in CPU architectures favours increasing the number of processing cores in lieu of improving the clock speed of an individual core. While improving clock rates automatically benefits any software executing on that processor, the same is not valid for adding new cores. To take advantage of an increased number of cores, software must include explicit support for parallel execution. This work explores a solu
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Xia, Shujiang. "An improved software process management tool: ReMoTe (recursively estimating multi-threaded observation tool enterprise)." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2871.

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The principal purpose of the project is to enable ReMoTe support for multi-databases. ReMoTe stands for the Recursively Estimating Multi-Threaded Observation Technology Enterprise, which is a web-based computer aided software engineering tool for monitoring software development process. Development of ReMoTe is based on the RMT (Recursive Multi-Threaded) software life cycle developed by Scott Simon, a CSUSB alum, in his master's thesis in 1997. ReMoTe enables the monitoring of projects that use different databases in various locations. Central management can view the progress information of ea
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Cattani, Philip Thomas. "Extending Cartesian genetic programming : multi-expression genomes and applications in image processing and classification." Thesis, University of Kent, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.655651.

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Genetic Programming (GP) is an Evolutionary Computation technique. Genetic Programming refers to a programming strategy where an artificial population of individuals represent solutions to a problem in the form of programs, and where an iterative process of selection and reproduction is used in order to evolve increasingly better solutions. This strategy is inspired by Charles Darwin's theory of evolution through the mechanism of natural selection. Genetic Programming makes use of computational procedures analogous to some of the same biological processes which occur in natural evolution, name
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Masimula, Steven Mandla. "Gene expression programming for logic circuit design." 2017. http://hdl.handle.net/10500/23617.

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Finding an optimal solution for the logic circuit design problem is challenging and time-consuming especially for complex logic circuits. As the number of logic gates increases the task of designing optimal logic circuits extends beyond human capability. A number of evolutionary algorithms have been invented to tackle a range of optimisation problems, including logic circuit design. This dissertation explores two of these evolutionary algorithms i.e. Gene Expression Programming (GEP) and Multi Expression Programming (MEP) with the aim of integrating their strengths into a new Genetic Prog
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Huang, Bo-Jyun, and 黃柏鈞. "Using Multi-Gene Expression Programming in the Prediction Model for Customer Churn：The Case of Laundry SMEs." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/73177801405833036542.

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碩士<br>輔仁大學<br>資訊管理學系<br>100<br>In recent years, the core of the enterprise strategy is gradually transformed into customer-centric, and the customer churn issues are taken seriously. However, with the information technology booming, customer information and transaction data has been accumulated surprisingly. It is exactly a good opportunity for SMEs （Small and medium enterprise, SMEs）to improve the ability of its IT applications. Customer information and transaction data implied customer behavior patterns. In so doing, a customer churn warming model helps enterprises to develop service strateg
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Book chapters on the topic "Improved multi expression programming"

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Deng, Wei, Pei He, and Zhi Huang. "Multi-Expression Based Gene Expression Programming." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38466-0_49.

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Zhang, Qingke, Xiangxu Meng, Bo Yang, and Weiguo Liu. "MREP: Multi-Reference Expression Programming." In Intelligent Computing Theories and Application. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42294-7_3.

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Liu, Xiaobo, Zhihua Cai, and Wenyin Gong. "An Improved Gene Expression Programming for Fuzzy Classification." In Advances in Computation and Intelligence. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92137-0_57.

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Oltean, Mihai, and D. Dumitrescu. "Evolving TSP Heuristics Using Multi Expression Programming." In Computational Science - ICCS 2004. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24687-9_99.

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Ávila, J. L., E. L. Gibaja, and S. Ventura. "Multi-label Classification with Gene Expression Programming." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02319-4_76.

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Oltean, Mihai, and Crina Groşan. "Evolving Evolutionary Algorithms Using Multi Expression Programming." In Advances in Artificial Life. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39432-7_70.

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Yang, Shuling, Kangshun Li, Wei Li, and Weiguang Chen. "An Optimized Clustering Algorithm Using Improved Gene Expression Programming." In Communications in Computer and Information Science. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0356-1_15.

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Deng, Wei, and Pei He. "Improving Multi Expression Programming Using Reuse-Based Evaluation." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34289-9_33.

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Groşan, Crina, Ajith Abraham, and and Sang Yong Han. "MEPIDS: Multi-Expression Programming for Intrusion Detection System." In Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11499305_17.

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Senthilnath, J., S. N. Omkar, V. Mani, Ashoka Vanjare, and P. G. Diwakar. "Multi-Temporal Satellite Image Analysis Using Gene Expression Programming." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1602-5_109.

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Conference papers on the topic "Improved multi expression programming"

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Wang, Yanan, Bo Yang, and Xiuyang Zhao. "Contour Registration Based on Multi-Expression Programming and the Improved ICP." In 2009 International Symposium on Computer Network and Multimedia Technology (CNMT 2009). IEEE, 2009. http://dx.doi.org/10.1109/cnmt.2009.5374777.

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Hadjam, Fatima Zohra, Claudio Moraga, and Mohamed Benmohamed. "Cluster-based evolutionary design of digital circuits using all improved multi-expression programming." In the 2007 GECCO conference companion. ACM Press, 2007. http://dx.doi.org/10.1145/1274000.1274013.

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Rudenko, Olga Valentinovna, and Andrey Aleksandrovich Kramarenko. "APPLICATION OF THE HARRINGTON DESIRE FUNCTION IN DESIGNING COMPLEX MULTI-COMPONENT FOOD." In XIII Международная научно-практическая конференция "Научные междисциплинарные исследования". KDU, Moscow, 2021. http://dx.doi.org/10.31453/kdu.ru.978-5-7913-1172-6-2021-63-72.

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The article discusses the issue of design automation and optimization of complex multicomponent food products using mathematical programming methods. Food design methods based on generalized modeling criteria with one vector of mixture quality indicators lead to the formulation of a quadratic programming problem. Determination of the universal quality indicator can be carried out using the asymmetric Harrington desirability functions. The application of the criterion with the specified lower and upper permissible levels of consumption for each of the quality indicators allows one to take into
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Grosan, Crina, Ajith Abraham, Vitorino Ramos, and Sang Yong Han. "Stock Market Prediction Using Multi Expression Programming." In 2005 Purtuguese Conference on Artificial Intelligence. IEEE, 2005. http://dx.doi.org/10.1109/epia.2005.341268.

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Cattani, Phil T., and Colin G. Johnson. "ME-CGP: Multi Expression Cartesian Genetic Programming." In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586478.

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Fu, Weizhong, Yuntao Zhang, and Zhengjun Cheng. "Improved gene expression programming and its application to QSAR." In 2010 Sixth International Conference on Natural Computation (ICNC). IEEE, 2010. http://dx.doi.org/10.1109/icnc.2010.5584850.

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Kejun Zhang, Yuxia Hu, and Gang Liu. "An Improved Gene Expression Programming for Solving Inverse Problem." In 2006 6th World Congress on Intelligent Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/wcica.2006.1712993.

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Wang, Weihong, Wenrou Lin, and Qu Li. "Image retrieval based on Multi Expression Programming algorithms." In 2013 9th International Conference on Natural Computation (ICNC). IEEE, 2013. http://dx.doi.org/10.1109/icnc.2013.6818191.

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Ma, Jun, Fenghui Gao, Shuangrong Liu, and Lin Wang. "Linear-dependent multi-interpretation neuro-encoded expression programming." In GECCO '21: Genetic and Evolutionary Computation Conference. ACM, 2021. http://dx.doi.org/10.1145/3449726.3459498.

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Nouri, Mostafa, and Jean W. Zu. "Dynamic Analysis and Optimization of Tensioner in Automotive Serpentine Belt Drive Systems." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/dac-34120.

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A design methodology is developed to achieve optimum design of tensioner in serpentine belt drive systems. System component responses to a harmonic excitation from the crankshaft are obtained analytically by using a complete multi-degree of freedom model and also in explicit expressions using an equivalent single-degree of freedom model. Sequential quadratic programming and Kuhn-Tucker methods are applied to obtain the optimum design of the system modeled as multi-degree of freedom and single-degree of freedom respectively, with the objective of minimizing the undesired vibration of system com
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Reports on the topic "Improved multi expression programming"

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Carter, Becky. Inclusion in Crisis Response, Recovery and Resilience. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.079.

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This rapid review provides examples of what has worked to include people in humanitarian assistance who experience heightened vulnerability during crises, due to social inequalities and discrimination relating to gender, age, disability, sexual orientation, gender identity and/or expression, and sex characteristics; and religious belief . Overall, robust evidence is limited for what are, in most cases, relatively new areas of practice in challenging crisis situations. However, the literature does identify promising practices. Emerging themes from the research on what has potential for improvin
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Amela, R., R. Badia, S. Böhm, R. Tosi, C. Soriano, and R. Rossi. D4.2 Profiling report of the partner’s tools, complete with performance suggestions. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.023.

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This deliverable focuses on the proling activities developed in the project with the partner's applications. To perform this proling activities, a couple of benchmarks were dened in collaboration with WP5. The rst benchmark is an embarrassingly parallel benchmark that performs a read and then multiple writes of the same object, with the objective of stressing the memory and storage systems and evaluate the overhead when these reads and writes are performed in parallel. A second benchmark is dened based on the Continuation Multi Level Monte Carlo (C-MLMC) algorithm. While this algorithm is norm
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