کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5009283 1462042 2017 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of decision tree based classification strategies to detect external chemical stimuli from raw and filtered plant electrical response
ترجمه فارسی عنوان
مقایسه راهکارهای طبقه بندی مبتنی بر درخت تصمیم برای شناسایی محرک های شیمیایی خارجی از پاسخ الکتریکی خاک و تصفیه شده
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی


- Ozone, Sulfuric Acid and Sodium Chloride have been classified using the plant signals.
- Several statistical features have been extracted from plant electrical response.
- A decision tree classier is developed based on discriminant analysis.
- Cross validation and independent validation accuracies have been reported.
- Most significant features and classifier setting have been reported for classifying environmental chemical stimuli.

Plants monitor their surrounding environment and control their physiological functions by producing an electrical response. We recorded electrical signals from different plants by exposing them to Sodium Chloride (NaCl), Ozone (O3) and Sulfuric Acid (H2SO4) under laboratory conditions. After applying pre-processing techniques such as filtering and drift removal, we extracted few statistical features from the acquired plant electrical signals. Using these features, combined with different classification algorithms, we used a decision tree based multi-class classification strategy to identify the three different external chemical stimuli. We here present our exploration to obtain the optimum set of ranked feature and classifier combination that can separate a particular chemical stimulus from the incoming stream of plant electrical signals. The paper also reports an exhaustive comparison of similar feature based classification using the filtered and the raw plant signals, containing the high frequency stochastic part and also the low frequency trends present in it, as two different cases for feature extraction. The work, presented in this paper opens up new possibilities for using plant electrical signals to monitor and detect other environmental stimuli apart from NaCl, O3 and H2SO4 in future.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sensors and Actuators B: Chemical - Volume 249, October 2017, Pages 278-295
نویسندگان
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