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Forecasting the Peak Demand Days of Chronic Respiratory Diseases with Fuzzy Logic

机译:用模糊逻辑预测慢性呼吸道疾病的高峰需求日。

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Chronic Respiratory Diseases are the diseases which affects respiratory tract and other parts of lung. Few of the most usual respiratory diseases are Chronic Obstructive Respiratory Diseases (COPD), asthma, occupational lung diseases and pulmonary hypertension. These mainly occur due to sudden climatic changes and health conditions of patients become worse once they are not detected early. Quick variations in weather conditions result in overcrowding of hospitals. In this paper, a fuzzy inference system is developed for prediction of higher possible days of chronic respiratory diseases considering various atmospheric parameters. This helps the Emergency Departments (EDs) in hospitals to prepare best medical facilities for the patients to be provided in time. Study was conducted at Kottayam in state of Kerala, India. The system was trained with fuzzy rules resulting in forecasting peak demand days of Chronic Respiratory Diseases. The fuzzy system was simulated in matlab.
机译:慢性呼吸系统疾病是影响呼吸道和肺其他部位的疾病。很少有最常见的呼吸道疾病是慢性阻塞性呼吸道疾病(COPD),哮喘,职业性肺病和肺动脉高压。这些主要是由于突然的气候变化而导致的,一旦不及早发现患者的健康状况就会恶化。天气条件的快速变化导致医院人满为患。在本文中,开发了一种模糊推理系统,用于在考虑各种大气参数的情况下预测慢性呼吸道疾病的更高可能发生日期。这有助于医院的急诊科(ED)为患者提供最佳的医疗设施,以便及时提供。研究在印度喀拉拉邦的科塔亚姆进行。该系统使用模糊规则进行了培训,可以预测慢性呼吸道疾病的需求高峰日。在matlab中对模糊系统进行了仿真。

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