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您的检索式：作者名="Rohit Bansal"
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| 1 | Improved automatic discovery of subgoals for options in hierarchical reinforcement learning 显示文摘 | R Matthew Kretchmar Todd Feil Rohit Bansal | 2003 | Journal of Computer Science and Technology (S1000-9000)2003，3，2： | 1 |
| 2 | DEPSOSVM:variant of differential evolution based on PSO for image and text data classification显示文摘Purpose-Feature selection is an important step for data pre-processing specially in the case of high dimensional data set.Performance of the data model is reduced if the model is trained with high dimensional data set,and it results in poor classification accuracy.Therefore,before training the model an important step to apply is the feature selection on the dataset to improve the performance and classification accuracy.Design/methodology/approach-A novel optimization approach that hybridizes binary particle swarm optimization(BPSO)and differential evolution(DE)for fine tuning of SVM classifier is presented.The name of the implemented classifier is given as DEPSOSVM.Findings-This approach is evaluated using 20 UCI benchmark text data classification data set.Further,the performance of the proposed technique is also evaluated on UCI benchmark image data set of cancer images.From the results,it can be observed that the proposed DEPSOSVMtechniques have significant improvement in performance over other algorithms in the literature for feature selection.The proposed technique shows better classification accuracy as well.Originality/value-The proposed approach is different from the previous work,as in all the previous work DE/(rand/1)mutation strategy is used whereas in this study DE/(rand/2)is used and the mutation strategy with BPSO is updated.Another difference is on the crossover approach in our case as we have used a novel approach of comparing best particle with sigmoid function.The core contribution of this paper is to hybridize DE with BPSO combined with SVM classifier(DEPSOSVM)to handle the feature selection problems. | Abhishek Dixit Ashish Mani Rohit Bansal | 2020 | International Journal of Intelligent Computing and Cybernetics2020，13，2： | 0 |
| 3 | Atrial fibrillation and dementia: not just a coincidence显示文摘Atrial fibrillation(AF)is the most common form of cardiac arrhythmia,affecting 3 to 6 million people in the US,with an increased incidence in women and elderly,with its prevalence estimated to increase from 5.1 million in 2000 to 15.9 million in 2050 in the US population.[1]Age,hypertension,heart failure,myocardial infarction(MI),genetic factors,and associated systemic inflammatory states are well-established risk factors for the development of AF.[2–6]Lifestyle factors including alcohol consumption,smoking,obesity,sedentary lifestyle,and vigorous physical activity have also been implicated to contribute to the development of AF.[2,7–9]Studies suggest that AF drives up medical expenditure.[10]The European Society of Cardiology,based on the duration,responsiveness to treatment,and therapeutic attitude of the patient and physician,classifies AF into 4 types;when AF occurs and terminates by itself or by intervention within 7 days of onset,it is called paroxysmal AF;if sustained for more than a week,with or without intervention. | Udit Choubey Vasu Bansal Priyanshi Shah FNU Anamika Vasu Gupta Sweta Sahu Miran Rezhan Rohit Jain | 2023 | Journal of Geriatric Cardiology2023，20，9： | 0 |
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