نتایج جستجو برای: gene expression programming gep
تعداد نتایج: 1912249 فیلتر نتایج به سال:
Classification is one of the fundamental tasks of data mining. Most rule induction and decision tree algorithms perform local, greedy search to generate classification rules that are often more complex than necessary. Evolutionary algorithms for pattern classification have recently received increased attention because they can perform global searches. In this paper, we propose a new approach fo...
Because of the limited environmental monitoring stations, the spatial data we have obtained by monitoring is local, discrete and limited. Therefore, speculating the environmental pollution parameters without monitoring station by using known monitoring data for spatial interpolation has become a hot research topic. In our preliminary work, an approach combining Genetic Expression Programming (G...
Fracture toughness is an important phenomenon to reveal the actual strength of fractured rock materials. It is, therefore, crucial use fracture models principally for simulating performance medium. In this study, mode-I (KIC) was investigated using several soft computing techniques. For purpose, extensive literature survey carried out obtain a comprehensive database that includes simple and wid...
BACKGROUND AND AIMS Increasing evidence has suggested that hepatocellular carcinoma (HCC) might originate from a distinct subpopulation called cancer stem cells (CSCs), which are responsible for the limited efficacy of conventional therapies. We have previously demonstrated that granulin-epithelin precursor (GEP), a pluripotent growth factor, is upregulated in HCC but not in the adjacent non-tu...
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...
Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 1...
precipitation is considered as one of the most important factures in water cycle. prediction of monthly precipitation is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins.in this study we studied and evaluated gene expression programming to predict the precipitation of the kakareza river (in lorestan...
In this study, the efficiency of neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the transfer length of prestressing strands in prestressed concrete beams was investigated. Many models suggested for the transfer length of prestressing strands usually consider one or two parameters and do not provide consistent accurate prediction. The alternative appr...
The NCCN Guidelines for Occult Primary tumors provide recommendations for the evaluation, workup, management, and follow-up of patients with occult primary tumors (cancers of unknown primary). These NCCN Guidelines Insights summarize major discussion points of the 2014 NCCN Occult Primary panel meeting. The panel discussed gene expression profiling (GEP) for the identification of the tissue of ...
BackgroundCurrent staging systems for cutaneous squamous cell carcinoma (cSCC) have limited positive predictive value identifying patients who will experience metastasis.ObjectiveTo develop and validate a gene expression profile (GEP) test predicting risk metastasis in localized, high-risk cSCC with the goal of improving risk-directed patient management.MethodsArchival formalin-fixed paraffin-e...
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