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BeECD: Belief-Aware Echo Chamber Detection over Twitter Stream
The phenomenon known as the “echo chamber” has been widely acknowledged as a significant force affecting society. This has been particularly evident...
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A framework for extended belief rule base reduction and training with the greedy strategy and parameter learning
The extended belief rule-based system has been used in the field of decision making in recent years for its advantage of expressing various kinds of...
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Kernel smoothing classification of multiattribute data in the belief function framework: Application to multichannel image segmentation
Bayesian approaches turn out to be inefficient when decision making involves many uncertain, imprecise or unreliable sources of information. The same...
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Underwater stereo-matching algorithm based on belief propagation
Using stereo-imaging systems to collect 3D information is innovative and flexible for underwater exploration. The stereo-matching of underwater image...
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A better and fast cloud intrusion detection system using improved squirrel search algorithm and modified deep belief network
Utilizing the cloud environment is one of the most preferable option in every information technology (IT) organization for running its business due...
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An algorithmic debugging approach for belief-desire-intention agents
Debugging agent systems can be rather difficult. It is often noted as one of the most time-consuming tasks during the development of cognitive...
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Deep belief network for solving the image quality assessment in full reference and no reference model
Image Quality Assessment (IQA) is one of the essential problems in image processing. The growth of natural image quality assessment methods has...
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An integrated 3D-sparse deep belief network with enriched seagull optimization algorithm for liver segmentation
PurposeLiver segmentation is an essential step in a variety of clinical applications like tumor detection, transplantation, and other liver...
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Splitting Techniques for Conditional Belief Bases in the Context of c-Representations
Splitting belief bases is fundamental for efficient reasoning and for better understanding interrelationships among the knowledge entities. In this...
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An ontology-based deep belief network model
The end-to-end model has a wide range of applications in the fields of image recognition, natural language processing and speech recognition. The...
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A Bayesian belief-rule-based inference multivariate alarm system for nonlinear time-varying processes
This study considers the multivariate alarm design problem of nonlinear time-varying systems by a Bayesian belief-rule-based (BRB) method. In the...
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Investigating the Use of Belief-Bias to Measure Acceptance of False Information
Belief-bias occurs when individuals’ prior beliefs impact their ability to judge the validity (i.e., structure) of an argument such that they are...
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An improved deep belief neural network based civil unrest event forecasting in twitter
Nowadays, event forecasting in Twitter can be considered an essential, significant and difficult issue. Maximum conventional methods are focusing on...
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Speech Expression Multimodal Emotion Recognition Based on Deep Belief Network
Aiming at the problems of insufficient information and poor recognition rate in single-mode emotion recognition, a multi-mode emotion recognition...
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Affordances-Based Behavior Change for Energy Efficiency Among Malaysians: A Conceptual Model
Climate change is a pressing global issue that affects countries worldwide. To mitigate its impacts, reducing carbon emissions is crucial. One...
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Generalized 3-Valued Belief States in Conformant Planning
The high complexity of planning with partial observability has motivated to find compact representations of belief state (sets of states) that reduce...
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New health-state assessment model based on belief rule base with interpretability
Health-state assessment is the foundation of optimal-maintenance decision-making for complex systems to maintain reliability and safety. Generating...
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Free Will Belief as a Consequence of Model-Based Reinforcement Learning
The debate on whether or not humans have free will has been raging for centuries. Although there are good arguments based on our current...
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Discrete collective estimation in swarm robotics with distributed Bayesian belief sharing
Multi-option collective decision-making is a challenging task in the context of swarm intelligence. In this paper, we extend the problem of...
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Spatio-temporal Data Analytics for e-Waste Management System Using Hybrid Deep Belief Networks
In the most recent few decades, there has been a significant increase all over the world in the amount of waste electronic equipment. This is a...