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Jeffrey Tim Query, Evaristo Diz
Pág. 145 - 159
AbstractIn this study we examine the robustness of fit for a multivariate and an autoregressive integrated moving average model to a data sample time series type. The sample is a recurrent actuarial data set for a 10-year horizon. We utilize ...
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Charles Gitiya Njoroge
Pág. 88 - 100
The purpose of the study was to establish the effect of exchange rate on the performance of the residential property market in Kenya. The study used secondary data that was accumulated using secondary data collection sheet from first quarter of 2005 to f...
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Yang Liu, Qiang Zhang, Longjin Wang, Shun An, Yan He, Zhimin Fan and Fang Deng
This paper investigates the problem of real-time parameter identification for ship maneuvering parameters and wave peak frequency in an ocean environment. Based on the idea of Euler discretion, a combined model of ship maneuvering and wave peak frequency...
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Patrick Toman, Nalini Ravishanker, Nathan Lally and Sanguthevar Rajasekaran
With the advent of the ?Internet of Things? (IoT), insurers are increasingly leveraging remote sensor technology in the development of novel insurance products and risk management programs. For example, Hartford Steam Boiler?s (HSB) IoT freeze loss progr...
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Pouya Hosseinzadeh, Ayman Nassar, Soukaina Filali Boubrahimi and Shah Muhammad Hamdi
Streamflow prediction plays a vital role in water resources planning in order to understand the dramatic change of climatic and hydrologic variables over different time scales. In this study, we used machine learning (ML)-based prediction models, includi...
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Achintya Kumar Sarkar and Zheng-Hua Tan
Deep representation learning has gained significant momentum in advancing text-dependent speaker verification (TD-SV) systems. When designing deep neural networks (DNN) for extracting bottleneck (BN) features, the key considerations include training targ...
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Zhao Wang, Ningjia Qiu, Peng Wang and Meng Li
In the prediction and modeling analysis of wear degree in the field of industrial parts processing, there are problems such as poor prediction ability for long sequence data and low sensitivity of output feedback to changes in input signals. In this pape...
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Ayushi Chahal, Preeti Gulia, Nasib Singh Gill and Ishaani Priyadarshini
IoT devices collect time-series traffic data, which is stochastic and complex in nature. Traffic flow prediction is a thorny task using this kind of data. A smart traffic congestion prediction system is a need of sustainable and economical smart cities. ...
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Ansari Saleh Ahmar, Pawan Kumar Singh, R. Ruliana, Alok Kumar Pandey and Stuti Gupta
The agriculture sector plays an essential function within the Indian economic system. Foodgrains provide almost all the calories and proteins. This paper aims to compare ARIMA, SutteARIMA, Holt-Winters, and NNAR models to recommend an effective model to ...
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Albert Larson, Abdeltawab Hendawi, Thomas Boving, Soni M. Pradhanang and Ali S. Akanda
The impact of climate change continues to manifest itself daily in the form of extreme events and conditions such as droughts, floods, heatwaves, and storms. Better forecasting tools are mandatory to calibrate our response to these hazards and help adapt...
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