Proceedings of the 10th annual conference on Genetic and evolutionary computation
ARIMA models versus gene expression programming in precipitation modeling
EC'09 Proceedings of the 10th WSEAS international conference on evolutionary computing
Adaptive genetic programming for dynamic classification problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A model of portfolio optimization using time adapting genetic network programming
Computers and Operations Research
An improved method of traffic forecasting based on tariff-SASVR
ICNC'09 Proceedings of the 5th international conference on Natural computation
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Open issues in genetic programming
Genetic Programming and Evolvable Machines
Adaptive time-variant models for fuzzy-time-series forecasting
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Polynomial modeling for time-varying systems based on a particle swarm optimization algorithm
Information Sciences: an International Journal
Long memory time series forecasting by using genetic programming
Genetic Programming and Evolvable Machines
Forecasting with a dynamic window of time: the DyFor genetic program model
IMTCI'04 Proceedings of the Second international conference on Intelligent Media Technology for Communicative Intelligence
A global-local optimization approach to parameter estimation of RBF-type models
Information Sciences: an International Journal
GP under streaming data constraints: a case for pareto archiving?
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Symbolic regression of multiple-time-scale dynamical systems
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Genetic programming needs better benchmarks
Proceedings of the 14th annual conference on Genetic and evolutionary computation
ACM Computing Surveys (CSUR)
Evolving event detectors in multi-channel sensor data
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
On the utility of trading criteria based retraining in forex markets
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Benchmarking pareto archiving heuristics in the presence of concept drift: diversity versus age
Proceedings of the 15th annual conference on Genetic and evolutionary computation
On the impact of streaming interface heuristics on GP trading agents: an FX benchmarking study
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Towards a dynamic benchmark for genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Nonlinear speech coding model based on genetic programming
Applied Soft Computing
On the investigation of hyper-heuristics on a financial forecasting problem
Annals of Mathematics and Artificial Intelligence
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Several studies have applied genetic programming (GP) to the task of forecasting with favorable results. However, these studies, like those applying other techniques, have assumed a static environment, making them unsuitable for many real-world time series which are generated by varying processes. This study investigates the development of a new ldquodynamicrdquo GP model that is specifically tailored for forecasting in nonstatic environments. This dynamic forecasting genetic program (DyFor GP) model incorporates features that allow it to adapt to changing environments automatically as well as retain knowledge learned from previously encountered environments. The DyFor GP model is tested for forecasting efficacy on both simulated and actual time series including the U.S. Gross Domestic Product and Consumer Price Index Inflation. Results show that the performance of the DyFor GP model improves upon that of benchmark models for all experiments. These findings highlight the DyFor GP's potential as an adaptive, nonlinear model for real-world forecasting applications and suggest further investigations.