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摘要:
Information collection from remote location is very important for several tasks such as temperate monitoring, air quality investigation, and wartime surveillance. Wireless sensor network is the first choice to complete these types of tasks. Basically, information prediction scheme is an important feature in any sensor nodes. The efficiency of the sensor network can be improved to large extent with a suitable information prediction scheme. Previously, there were several efforts to resolve this problem, but their accuracy is decreased as the prediction threshold reduces to a small value. Our proposed Adams-Bashforth-Moulton algorithm to overcome this drawback was compared with the Milne Simpson scheme. The proposed algorithm is simulated on distributed sensor nodes where information is gathered from the Intel Berkeley Research Laboratory. To maximize the power saving in wireless sensor network, our adopted method achieves the accuracy of 60.28 and 59.2238 for prediction threshold of 0.01 for Milne Simpson and Adams-Bashforth-Moulton algorithms, respectively.
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篇名 Data Prediction in Distributed Sensor Networks Using Adam Bashforth Moulton Method
来源期刊 传感技术(英文) 学科 医学
关键词 Adams-Bashforth-Moulton METHOD Energy SAVING Milne-Simpson METHOD WIRELESS Sensor Networks
年,卷(期) 2018,(2) 所属期刊栏目
研究方向 页码范围 48-57
页数 10页 分类号 R73
字数 语种
DOI
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Adams-Bashforth-Moulton
METHOD
Energy
SAVING
Milne-Simpson
METHOD
WIRELESS
Sensor
Networks
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期刊影响力
传感技术(英文)
季刊
2161-122X
武汉市江夏区汤逊湖北路38号光谷总部空间
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114
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0
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