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Applying MAPE-K control loops for adaptive workflow management in smart factories
Monitoring the state of currently running processes and reacting to ad-hoc situations during runtime is a key challenge in Business Process Management...
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MAPE-K patterns for self-adaptation in cyber-physical systems
Cyber-physical systems (CPS) are characterized with their concurrency, heterogeneity and time sensitivity. In this context, it is crucial to have...
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Analysis of MAPE-K Loop in Self-adaptive Systems for Cloud, IoT and CPS
Self-adaptive approaches aim to address the complexity of modern computing generated by the runtime variabilities and uncertainties. In this context,...
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Modeling and specifying formally compound MAPE pattern for self-adaptive IoT systems
IoT systems are required to manage themselves to changes regarding their internal and external contexts. So, adaptability is a very important aspect...
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DeepCov: Effective Prediction Model of COVID-19 Using CNN Algorithm
COVID-19 outbreak prediction is a challenging and complicated problem in a vast dataset. Several communities have proposed various methods to predict...
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Multivariate time series ensemble model for load prediction on hosts using anomaly detection techniques
Host load prediction is essential in computing to improve resource utilization and for achieving service level agreements. However, due to variations...
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An empirical cryptocurrency price forecasting model
The goal of this manuscript is to use deep learning based multi-modal hybrid model to forecast the value of bitcoins by analyzing the influence of...
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DTM-GCN: A traffic flow prediction model based on dynamic graph convolutional network
A traffic network possesses all the basic characteristics of networks, as well as its own distinct features, which have research significance. In...
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Forecasting PM2.5 Concentration Using Gradient-Boosted Regression Tree with CNN Learning Model
AbstractAir pollution imposed by particle matter (PM) made it a public health concern and hazard to humans and the environment. Reduced vision,...
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Medium-Term AQI Prediction in Selected Areas of Bangladesh Based on Bidirectional GRU Network Model
Currently, Bangladesh is among the countries with the highest levels of air pollution in the world. Major cities of Bangladesh experience severe air...
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AQIPred: A Hybrid Model for High Precision Time Specific Forecasting of Air Quality Index with Cluster Analysis
The discipline of forecasting and prediction is witnessing a surge in the application of these techniques as a direct result of the strong empirical...
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Deep ensemble model with hybrid intelligence technique for crop yield prediction
Over 50% of India's population relies on crop growing, making it the foundation of the country's economy. Differences in weather, temperature, and...
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PowerDis: Fine-Grained Power Monitoring Through Power Disaggregation Model
In an era where power and energy are the first-class constraints of computing systems, precise power information is crucial for energy efficiency...
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A Support Vector Based Hybrid Forecasting Model for Chaotic Time Series: Spare Part Consumption Prediction
Reliability of spare parts inventory in the company is one of the most significant challenges in the field of maintenance and repairs, but on the...
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An autonomous planning model for solving IoT service placement problem using the imperialist competitive algorithm
The growth of the Internet of Things (IoT) can lead to improved productivity, scalability, connectivity, and saving time and money. However, the...
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Forecasting the Price of Bitcoin Using an Explainable CNN-LSTM Model
Artificial Intelligence (AI) significantly improves time series forecasting in the financial market, yet it is challenging to establish reliable...
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Stock market prediction with political data Analysis (SP-PDA) model for handling big data
The ability to accurately predict the stock market is a crucial financial topic. The basic assumption is that future stock returns can be somewhat...
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TASE-Net: A Short-Term Load Forecasting Model Based on Temperature Accumulation Sequence Effect
Electricity consumption forecasting plays an important role in ensuring efficient dispatch and reliability of the grid. The results are influenced by...
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Research on Soil Moisture Prediction Based on LSTM-Transformer Model
Soil moisture is one of the basic climate variables of the global climate observation system, and the prediction of soil moisture is of great...