{"title":"Adaptive genetic programming applied to classification in data mining","authors":"Nailah Al-Madi, Simone A. Ludwig","doi":"10.1109/NaBIC.2012.6402243","DOIUrl":"https://doi.org/10.1109/NaBIC.2012.6402243","url":null,"abstract":"Classification is a data mining method that assigns items in a collection to target classes with the goal to accurately predict the target class for each item in the data. Genetic programming (GP) is one of the effective evolutionary computation techniques to solve classification problems, however, it suffers from a long run time. In addition, there are many parameters that need to be set before the GP is run. In this paper, we propose an adaptive GP that automatically determines the best parameters of a run, and executes the classification faster than standard GP. This adaptive GP has three variations. The first variant consists of an adaptive selection process ensuring that the produced solutions in the next generation are better than the solutions in the previous generation. The second variant adapts the crossover and mutation rates by modifying the probabilities ensuring that a solution with a high fitness is protected. And the third variant is an adaptive function list that automatically changes the functions used by deleting the functions that do not favorably contribute to the classification. These proposed variations were implemented and compared to the standard GP. The results show that a significant speedup can be achieved by obtaining similar classification accuracies.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134505739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A building block conservation and extension mechanism for improved performance in Polynomial Symbolic Regression tree-based Genetic Programming","authors":"Anisa W. Ragalo, N. Pillay","doi":"10.1109/NaBIC.2012.6402250","DOIUrl":"https://doi.org/10.1109/NaBIC.2012.6402250","url":null,"abstract":"Polynomial Symbolic Regression tree-based Genetic Programming faces considerable obstacles towards the discovery of a global optimum solution; three of these being bloat, premature convergence and a compromised ability to retain building block information. We present a building block conservation and extension strategy that targets these specific obstacles. Experiments conducted demonstrate a superior performance of our strategy relative to the canonical GP. Further our strategy achieves a competitive reduction in bloat.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131246085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ant Colony System based approach to single machine scheduling problems: Weighted tardiness scheduling problem","authors":"A. Madureira, D. Falcao, I. Pereira","doi":"10.1109/NaBIC.2012.6402244","DOIUrl":"https://doi.org/10.1109/NaBIC.2012.6402244","url":null,"abstract":"The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122511988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Neural oscillator for gait command of a humanoid robot","authors":"R. C. Paiva, A. Romariz, G. Borges","doi":"10.1109/NaBIC.2012.6402249","DOIUrl":"https://doi.org/10.1109/NaBIC.2012.6402249","url":null,"abstract":"In this article bio-inspired techniques are used for generating the gait of a biped robot. The concept of CPG, central pattern generator, which is a neural network capable of producing rhythm output, was used. It was modeled as coupled oscillators. With the purpose of verifying the operation of the oscillators, simulations were made. After that they were implemented for generating the gait for the robot. The output of the oscillators were used as the reference trajectory for the feet and the joint angles were obtained by inverse kinematics. We obtained good result in simulations for the humanoid robot, which showed a degree of tolerance to external perturbations.","PeriodicalId":103091,"journal":{"name":"2012 Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125376883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}