Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Alternative algorithms for the GPS static positioning solution
Applied Mathematics and Computation
Symbolic Regression via Genetic Programming
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
Robust polynomial neural networks in quantative-structure activity relationship studies
Systems Analysis Modelling Simulation - Special issue: Self-organising modelling and simulation
Genetic programming in classifying large-scale data: an ensemble method
Information Sciences: an International Journal - Special issue: Soft computing data mining
A (\mu + \lambda) - GP Algorithm and its use for Regression Problems
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Genetic subgradient method for solving location-allocation problems
Applied Soft Computing
Location Estimation via Support Vector Regression
IEEE Transactions on Mobile Computing
Aggregate a posteriori linear regression adaptation
IEEE Transactions on Audio, Speech, and Language Processing
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
Regularization approach to inductive genetic programming
IEEE Transactions on Evolutionary Computation
Implementing linear models in genetic programming
IEEE Transactions on Evolutionary Computation
GP ensembles for large-scale data classification
IEEE Transactions on Evolutionary Computation
A controlled genetic programming approach for the deceptive domain
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Simplified Dual Neural Network for Quadratic Programming With Its KWTA Application
IEEE Transactions on Neural Networks
Discovering approximate expressions of GPS geometric dilution of precision using genetic programming
Advances in Engineering Software
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Transformation of coordinates usually invokes level-wised processes wherein several sets of complicated equations are calculated. Unfortunately, the accuracy may be corrupted due to the accumulation of inevitable errors between the transformation processes. This paper presents a genetic-based method for generating regressive models for direct transformation from global positioning system (GPS) signals to 2-D coordinates. Since target coordinates for a GPS application can be obtained by using simpler transformation formulas, the computational costs and inaccuracy can be reduced. The proposed method, though does not exclude systematic errors due to the imperfection on defining the reference ellipsoid and the reliability of GPS receivers, effectively reduces the statistical errors when the accurate Cartesian coordinates are known from the independent sources. From the experimental results where the target datums TWD67 is investigated, it seems that the proposed method can serve as a direct and feasible solution to the transformation of GPS coordinates.