Shannon information theory a useful tool for detecting significant abiotic factors influencing the population dynamics of Helicoverpa armigera (Hübner) on cotton crop

Pratheepa, M.; Verghese, Abraham; Bheemanna, H.

doi:10.1016/j.ecolmodel.2016.06.003

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…Pratheepa et al . (2016) used Shannon's information theory (SIT) to find significant factors that affect H. armigera incidence. The results showed that correlation analysis revealed that crop stage is negatively correlated with pest population, which is true because the H. armigera population started to increase when the crop was in an earlier stage of fruiting and boll formation, and started to decline when the crop was in boll-bursting stage.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, Pratheepa et al . (2016) used data mining to find the significant factors that affect the incidence of the pest H. armigera . The authors considered for the analysis, as incidence factors, the crop stage of the cotton, season and abiotic factors such as maximum temperature, minimum temperature, morning relative humidity, evening relative humidity, rainfall and number of rainy days in a week.…”

Section: Resultsmentioning

confidence: 99%

“…In addition to computer vision, sensors (e.g. temperature sensors, soil and moisture sensors) allow data acquisition for analysis and predictions (Pratheepa et al ., 2016).…”

Section: Introductionmentioning

confidence: 99%

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Artificial-intelligence and sensing techniques for the management of insect pests and diseases in cotton: a systematic literature review

et al. 2022

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Integrated pest management (IPM) seeks to minimize the environmental impact of pesticide application, and reduce risks to human and animal health. IPM is based on two important aspects – prevention and monitoring of diseases and insect pests – which today are being assisted by sensing and artificial-intelligence (AI) techniques. In this paper, we surveyed the detection and diagnosis, with AI, of diseases and insect pests, in cotton, which have been published between 2014 and 2021. This research is a systematic literature review. The results show that AI techniques were employed – mainly – in the context of (i) classification, (ii) image segmentation and (iii) feature extraction. The most used algorithms, in classification, were support vector machines, fuzzy inference, back-propagation neural-networks and recently, convolutional neural networks; in image segmentation, k-means was the most used; and, in feature extraction, histogram of oriented gradients, partial least-square regression, discrete wavelet transform and enhanced particle-swarm optimization were equally used. The most used sensing techniques were cameras, and field sensors such as temperature and humidity sensors. The most investigated insect pest was the whitefly, and the disease was root rot. Finally, this paper presents future works related to the use of AI and sensing techniques, to manage diseases and insect pests, in cotton; for instance, implement diagnostic, predictive and prescriptive models to know when and where the diseases and insect pests will attack and make strategies to control them.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Artificial-intelligence and sensing techniques for the management of insect pests and diseases in cotton: a systematic literature review

et al. 2022

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“…However, considering the dynamic features of social development, the characteristics of contemporary social requirements, and the different talent cultivation goals of modern higher education, it is still of certain necessity to further discuss the existing research results, in especial, it's of important significance to create a set of appraisal systems and models to measure the teaching competence of university teachers in English major. To this end, this paper concludes and optimizes the existing research findings, establishes a novel system for measuring the said teaching competence combining with AHP and the Shannon Information Theory [17][18][19][20], and proposes an improved model for measuring the said competence, in the hopes of offering a useful evidence for enhancing the teaching competence of university teachers in English major. In this paper, the research content is organized into 5 chapters.…”

Section: Introductionmentioning

confidence: 91%

Strategies to Enhance the Teaching Competence of University Teachers in English Major

Xiang

2021

Int. J. Emerg. Technol. Learn.

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This paper aims to find strategies to improve the teaching ability of college teachers in English major, which is affected by various factors. Firstly, the teaching ability deficiencies of college teachers in English major were analyzed, and the connotations of this ability were summarized. On this basis, a novel measurement system was established for the teaching ability of college teachers in English major. Then, analytical hierarchy process (AHP) was combined with Shannon’s information theory into an improved model to measure the said teaching ability. In addition, several strategies were presented to improve teaching ability of college teachers in English major. The research results provide a good guide for the teaching reform in English major.

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“…Since its introduction, it has been a powerful tool to quantify information and has been applied in many other areas. 35–39…”

Section: Preliminariesmentioning

confidence: 99%

Interaction analysis–based information modeling of complex electromechanical systems in the processing industry

Wang

Gao

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part I:

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Information modeling for complex electromechanical systems in the processing industry is the foundation for system vulnerability analysis, failure propagation mechanism, and fault root cause tracing driven by data analysis. Focusing on the difficulties in information modeling for complex electromechanical systems, a new approach based on interaction analysis and a general framework for information modeling of complex electromechanical systems are proposed. First, the basic structures of the information model are defined based on monitoring data. Second, an improved symbolic transfer entropy method with procedures for optimizing the number of symbols, phase space reconstruction, binary encoding, and decimal decoding are proposed to detect the interaction direction and quantify the interaction strength between different monitoring variables. Third, some optional methods are introduced to simplify and modify models. Finally, a directed-weighted information model for a specific complex electromechanical system is constructed based on information flow. An actual information modeling application of a complex electromechanical system is used to demonstrate the proposed method and compare it with existing methods. This new approach can handle general information modeling problems and overcome the drawbacks of existing methods since all the monitoring variables are used to improve integrity of the model, and prior knowledge about the physical structure and key points’ selection are not required. A unique and complete information model is obtained regardless of the choice of the initial variable. Thus, the proposed method can be flexibly and effectively used in information modeling for complex electromechanical systems in the processing industry and formulate the foundation of system vulnerability analysis, failure propagation mechanism, and fault root cause tracing methodology, as well as other engineering applications.

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Shannon information theory a useful tool for detecting significant abiotic factors influencing the population dynamics of Helicoverpa armigera (Hübner) on cotton crop

Cited by 7 publications

References 13 publications

Artificial-intelligence and sensing techniques for the management of insect pests and diseases in cotton: a systematic literature review

Artificial-intelligence and sensing techniques for the management of insect pests and diseases in cotton: a systematic literature review

Strategies to Enhance the Teaching Competence of University Teachers in English Major

Interaction analysis–based information modeling of complex electromechanical systems in the processing industry

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