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Design of flexible neural trees using multi expression programming
2008 Chinese Control and Decision Conference, 2008Automatic designing of both architecture and parameters of an artificial neural network is an important problem. This paper introduces a new approach for designing artificial neural networks using multi expression programming (MEP-NN). The approach employs the multi expression programming to evolve the architecture and the parameters encoded in the ...
null Yuehui Chen +2 more
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Parallel Multi-objective Gene Expression Programming Based on Area Penalty
2008 International Conference on Computer Science and Information Technology, 2008Evolutionary algorithms are particularly desirable to solve multi-objective optimization problems. To improve the evolutionary efficiency, parallel multi-objective gene expression programming based on area penalty (PGEP-AP) is proposed in this paper. The main contributions include: (1) proposing the parallel multi-objective gene expression programming (
Jiang Wu +5 more
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MEPIDS: Multi-Expression Programming for Intrusion Detection System
2005An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. An IDS does not eliminate the use of preventive mechanism but it works as the last defensive mechanism in securing the system.
Crina Groşan +2 more
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Predicting Cement Compressive Strength Using Double-Layer Multi-expression Programming
2012 Fourth International Conference on Computational and Information Sciences, 2012This paper presents a novel algorithm named Double-layer Multi-expression Programming (DMEP). Then DMEP model is applied to the prediction of 28-day Portland cement compressive strength. We compare DMEP model with other four soft computing models, namely Multi-Expression Programming model (MEP), Gene Expression Programming model (GEP), Neural Networks ...
Qingke Zhang +3 more
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Gene Expression Programming with Multi-Threading Evaluation and Gene-Reuse Strategy
Proceedings of the 2020 4th International Conference on High Performance Compilation, Computing and Communications, 2020As an approach widely used in automatic programming, the efficiency of the traditional GEP algorithm has gradually failed to meet the needs of users since its bottleneck in the evaluation phase. In this paper, a novel strategy named Gene-Reuse is proposed to improve the efficiency of GEP. In contrast to the traditional evaluation phase of GEP, the Gene-
Lan YongShun, He Pei
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Multi-objective Gene Expression Programming Based Automatic Clustering Method
2018We have proposed multi-objective Gene Expression Programming (GEP) based automatic clustering method (do not need prior knowledge), which is denoted as MOGEPC. In our algorithm, we adopt GEP based multi-objective optimization, which has a powerful global search ability to optimize the two objective functions, namely, compactness and connectedness ...
Ruochen Liu, Jianxia Li, Manman He
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Multi-Temporal Satellite Image Analysis Using Gene Expression Programming
2014This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region.
J. Senthilnath +4 more
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MERGE: A Novel Evolutionary Algorithm Based on Multi Expression Gene Programming
2008 Fourth International Conference on Natural Computation, 2008Gene expression programming (GEP) is a new member in genetic computing. The traditional GEP lacks the power to handle very complex function mining problems due to its limited express capability. To solve the problem, this paper presents a new evolutionary algorithm named multi expression gene programming (MERGE).
Shucheng Dai +6 more
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A gene expression programming approach for evolving multi-class image classifiers
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2017This paper presents a methodology to perform multi-class image classification using Gene Expression Programming(GEP) in both balanced and unbalanced datasets. Descriptors are extracted from images and then their dimensionality are reduced by applying Principal Component Analysis.
Nelson Marcelo Romero Aquino +4 more
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