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mViSE: A visual search engine for analyzing multiplex IHC brain tissue images (spatial proteomics). [PDF]

Sci Rep
Huang L, Mills R, Mandula S, Bai L, Jeyhani M, Redell J, Nguyen H, Prasad S, Maric D, Roysam B.   +9 more
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Author Correction: Optimizing ternary hybrid nanofluids using neural networks, gene expression programming, and multi-objective particle swarm optimization: a computational intelligence strategy. [PDF]

Sci Rep
Hai T, Basem A, Alizadeh A, Singh PK, Rajab H, Maatki C, Becheikh N, Kolsi L, Singh NSS, Maleki H.   +9 more
europepmc   +1 more source

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Consolidation assessment using Multi Expression Programming

Applied Soft Computing, 2020
Abstract In this study, new approximate solutions for consolidation have been developed in order to hasten the calculations. These solutions include two groups of equations, one can be used to calculate the average degree of consolidation and the other one for computing the time factor (inverse functions).
Sohrab Sharifi, Saeed Abrishami, Amir H. Gandomi   +2 more
openaire   +3 more sources

Performing multi-target regression via gene expression programming-based ensemble models

Neurocomputing, 2021
Abstract Multi-Target Regression problem comprises the prediction of multiple continuous variables given a common set of input features, unlike traditional regression tasks, where just one output target is available. There are two major challenges when addressing this problem, namely the exploration of the inter-target dependencies and the modeling ...
Jose M. Moyano, Oscar Reyes, Habib M. Fardoun, Sebastián Ventura   +3 more
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Linear-dependent multi-interpretation neuro-encoded expression programming

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021
Neuro-Encoded Expression Programming (NEEP) implements the continuous coding for the discrete solution through recurrent neural networks (RNNs), and smooths sharpness of the discrete coding. However, the insertion model generating linear coding in NEEP breaks the coherence of linear coding of RNNs, because the resulting symbols tend to be cluttered ...
Jun Ma, Fenghui Gao, Shuangrong Liu, Lin Wang   +3 more
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Indirect estimation of resilient modulus (Mr) of subgrade soil: Gene expression programming vs multi expression programming

Structures
Laiba Khawaja, Muhammad Faisal Javed, Usama Asif, Loai Alkhattabi, Bilal Ahmed, Hisham Alabduljabbar   +5 more
openaire   +3 more sources

ME-CGP: Multi Expression Cartesian Genetic Programming

IEEE Congress on Evolutionary Computation, 2010
Cartesian Genetic Programming (CGP) is a form of Genetic Programming that uses directed graphs to represent programs. In this paper we propose a way of structuring a CGP algorithm to make use of the multiple phenotypes which are implicitly encoded in a genome string.
Phil T. Cattani, Colin G. Johnson
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Stock Market Prediction Using Multi Expression Programming

2005 portuguese conference on artificial intelligence, 2005
The use of intelligent systems for stock market predictions has been widely established. In this paper, we introduce a genetic programming technique (called multi-expression programming) for the prediction of two stock indices. The performance is then compared with an artificial neural network trained using Levenberg-Marquardt algorithm, support vector
Crina Grosan, Ajith Abraham, Vitorino Ramos, Sang Yong Han   +3 more
openaire   +1 more source