The Strategies to Improve Performance of Function Mining By Gene Expression Programming -Genetic Modifying, Overlapped Gene, Backtracking and Adaptive Mutation
نویسندگان
چکیده
This paper introduces the technologies to improve the performance of function mining by Gene Expression Programming (GEP) developed in Sichuan University last year. The main results include: (a) Genetic Modifying Algorithm (Trans-gene). By injection gene segment into genome, it guides the evolutional direction and speeds up knowledge discovery process. (b) Overlapped gene expression. Borrowing the idea of overlap gene expression from biological study, it applies overlapped gene expression, saves space for gene expression. (c) Backtrack-able GEP. Enlightened by atavism in biology, it proposes backtrack-able GEP algorithms, designing Geometric Proportion Increased Checkpoint Sequence and Accelerated Increased Checkpoint Sequence to restrict the backtrack process. (d) Adaptive Mutation. The mutation rate for each individual can vary in evolution according to the value of fitness. Experiments show that these techniques boost the performance of GEP by one or two magnitudes, respectively. Keyword Template Knowledge discover, Gene Expression Programming, Function Mining 1 This work was supported by the National Science Foundation of China under Grant No.60473071, the National Research Foundation for the Doctoral Program by the Chinese Ministry of Education under Grant No.20020610007.
منابع مشابه
Airfoil Shape Optimization with Adaptive Mutation Genetic Algorithm
An efficient method for scattering Genetic Algorithm (GA) individuals in the design space is proposed to accelerate airfoil shape optimization. The method used here is based on the variation of the mutation rate for each gene of the chromosomes by taking feedback from the current population. An adaptive method for airfoil shape parameterization is also applied and its impact on the optimum desi...
متن کاملPrediction of Blasting Cost in Limestone Mines Using Gene Expression Programming Model and Artificial Neural Networks
The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, and air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone mines in Iran using the artificial neural networks (ANNs), gene expression programming (G...
متن کاملThe Relationship between Mutation in HOXB1 Gene and Acute Myeloid Leukemia
Background: HOX genes are an exceedingly preserved family of homeodomain-involving transcription factors. They are related to a number of malignancies, comprising acute myeloid leukemia (AML). This study aimed to evaluate the effect of HOXB1 7bp deletion mutation on HOXB1gene expression in 36 individuals. Materials and Methods: The present cross-sectional study was done on a large Iranian fami...
متن کاملForecasting copper price using gene expression programming
Forecasting the prices of metals is important in many aspects of economics. Metal prices are also vital variables in financial models for revenue evaluation, which forms the basis of an effective payment regime using resource policymakers. According to the severe changes of the metal prices in the recent years, the classic estimation methods cannot correctly estimate the volatility. In order to...
متن کاملPrediction of Acid Mine Drainage Generation Potential of A Copper Mine Tailings Using Gene Expression Programming-A Case Study
This work presents a quantitative predicting likely acid mine drainage (AMD) generation process throughout tailing particles resulting from the Sarcheshmeh copper mine in the south of Iran. Indeed, four predictive relationships for the remaining pyrite fraction, remaining chalcopyrite fraction, sulfate concentration, and pH have been suggested by applying the gene expression programming (GEP) a...
متن کامل