Internet-Based Intelligent Information Processing Systems

Howlett, Robert J.; Ichalkaranje, Nikhil; Jain, Lokesh; Tonfoni, Graziella

doi:10.1142/5204

Cited by 6 publications

(3 citation statements)

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“…Various splitting strategies can be applied to train the model and test its performance [54,55]. The validity of the learned model is different from the algorithm validity.…”

Section: Performance Measures and Validation Methodsmentioning

confidence: 99%

Coparison of artificial intelligence methods for predicting compressive strength of concrete

Cihan¹

2021

JCE

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Compressive strength of concrete is an important parameter in concrete design. Accurate prediction of compressive strength of concrete can lower costs and save time. Therefore, thecompressive strength of concrete prediction performance of artificial intelligence methods (adaptive neuro fuzzy inference system, random forest, linear regression, classification and regression tree, support vector regression, k-nearest neighbour and extreme learning machine) are compared in this study using six different multinational datasets. The performance of these methods is evaluated using the correlation coefficient, root mean square error, mean absolute error, and mean absolute percentage error criteria. Comparative results show that the adaptive neuro fuzzy inference system (ANFIS) is more successful in all datasets.

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“…Various splitting strategies can be applied to train the model and test its performance [54,55]. The validity of the learned model is different from the algorithm validity.…”

Section: Performance Measures and Validation Methodsmentioning

confidence: 99%

Coparison of artificial intelligence methods for predicting compressive strength of concrete

Cihan¹

2021

JCE

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“…AI has numerous applications across various industries, including the petrochemical sector [13]. In the petrochemical industry, AI has a broader area of applications, like process optimization, predictive maintenance, fault detection and diagnosis, real-time monitoring, and control [14,15]. AI-based control techniques have gained significant attention in recent years due to dealing with complex and dynamic systems [16].…”

Section: Introductionmentioning

confidence: 99%

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

Ansari

Taqvi

2023

ChemBioEng Reviews

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Petrochemical industries are facing severe challenges in controlling nonlinear processes which are to be analyzed and monitored to develop efficient control models for improved efficiency and productivity. This review focuses on the control theory of petrochemical processes along with linear and nonlinear controllers with their limitations as well as on the application of artificial intelligence (AI)‐based controllers in multiple sectors of petrochemical industries. The findings and results from the review prove that the AI control technique is a promising one in the future for uncertain dynamic systems. The paper also covers a review of the vinyl chloride monomer (VCM) process and a recent control study on the plant. Being a nonlinear system, VCM requires advanced control techniques to control the uncertain dynamics of the process. The study shows a gap in the development of control strategies applied to VCM in terms of sustainability, efficiency, and environment‐concerned issues. Valuable insights for researchers, practitioners, and engineers engaged in process control and automation in the petrochemical industry are provided.

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“…This is chiefly due to the growing number of devices connected to the Internet, including mobile phones, computers and tablets as well as other types of smart devices, Bfrom minuscule chips to mammoth machines that use wireless technology to talk to each other (and to us)^ [16]. This hard to imagine source of big data, mainly represented by images and video sequences (the most rapidly-growing types of media), provides incredible but real opportunities for building heterogeneous intelligence systems [10]. The first issues which need to be addressed are content-oriented data analysis, enrichment, retrieval and recommendation.…”

Section: Introductionmentioning

confidence: 99%

A capable multimedia content discovery platform based on visual content analysis and intelligent data enrichment

Baran

Dziech

Zeja

2017

Multimed Tools Appl

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A new capable content discovery platform based on multimedia data enrichment is presented in this paper. The platform, known as the IMCOP system, refers to the concept of intelligent discovery and delivery of multimedia content. Relevant stateof-the-art solutions are described in detail in the background section. The overall architecture and the main components of the IMCOP system are presented next. An original concept of Complex Multimedia Objects which extend the MPEG-7 standard to hold the processed data and bind it into content related collections is introduced. Selected results of tests illustrating how the IMCOP system performs in terms of responsiveness and stability under a particular workload are reported. Finally, IMCOP's advantages in reference to other content discovery platforms are discussed and summed up.

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Internet-Based Intelligent Information Processing Systems

Cited by 6 publications

References 0 publications

Coparison of artificial intelligence methods for predicting compressive strength of concrete

Coparison of artificial intelligence methods for predicting compressive strength of concrete

State‐of‐the‐Art Review on the Applications of Nonlinear and Artificial Intelligence‐Based Controllers in Petrochemical Processes

A capable multimedia content discovery platform based on visual content analysis and intelligent data enrichment

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