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1 – 6 of 6Yuejiang Li, H. Vicky Zhao and Yan Chen
With the popularity of the internet and the increasing numbers of netizens, tremendous information flows are generated daily by the intelligently interconnected individuals. The…
Abstract
Purpose
With the popularity of the internet and the increasing numbers of netizens, tremendous information flows are generated daily by the intelligently interconnected individuals. The diffusion processes of different information are not independent, and they interact with and influence each other. Modeling and analyzing the interaction between correlated information play an important role in the understanding of the characteristics of information dissemination and better control of the information flows. This paper aims to model the correlated information diffusion process over the crowd intelligence networks.
Design/methodology/approach
This study extends the classic epidemic susceptible–infectious–recovered (SIR) model and proposes the SIR mixture model to describe the diffusion process of two correlated pieces of information. The whole crowd is divided into different groups with respect to their forwarding state of the correlated information, and the transition rate between different groups shows the property of each piece of information and the influences between them.
Findings
The stable state of the SIR mixture model is analyzed through the linearization of the model, and the stable condition can be obtained. Real data are used to validate the SIR mixture model, and the detailed diffusion process of correlated information can be inferred by the analysis of the parameters learned through fitting the real data into the SIR mixture model.
Originality/value
The proposed SIR mixture model can be used to model the diffusion of correlated information and analyze the propagation process.
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Haotian Xu, Jingcheng Wang, Hongyuan Wang, Ibrahim Brahmia and Shangwei Zhao
The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.
Abstract
Purpose
The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.
Design/methodology/approach
Motivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved.
Findings
The proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions.
Originality/value
The new method concerning design POCF has better plants compatibility and less validation conditions.
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Peiqing Li, Taiping Yang, Hao Zhang, Lijun Wang and Qipeng Li
This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion.
Abstract
Purpose
This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion.
Design/methodology/approach
In this paper the vehicle presighting and kinematic models were established, and a new sliding mode control isokinetic convergence law was devised based on the fractional order calculus to make the front wheel turning angle approach the desired value quickly. On this basis, a fractional gradient descent algorithm was proposed to adjust the radial basis function (RBF) neuron parameter update rules to improve the compensation speed of the neural network.
Findings
The simulation results revealed that, compared to the traditional sliding mode control strategy, the designed controller eliminated the jitter of the sliding mode control, sped up the response of the controller, reduced the overshoot of the system parameters and facilitated accurate and fast tracking of the desired path when the vehicle changed lanes at low speeds.
Originality/value
This paper combines the idea of fractional order calculus with gradient descent algorithm, proposed a fractional-order gradient descent method applied to RBF neural network and fast adjustment the position and width of neurons.
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Alexander Nikolaevich Raikov and Massimiliano Pirani
The purpose of the paper is to propose an effective approach of artificial intelligence (AI) addressing social-humanitarian reality comprising non-formalizable representation. The…
Abstract
Purpose
The purpose of the paper is to propose an effective approach of artificial intelligence (AI) addressing social-humanitarian reality comprising non-formalizable representation. The new task is to describe processes of integration of AI and humans in the hybrid systems framework.
Design/methodology/approach
Social-humanitarian dynamics contradict traditional characteristics of AI. Suggested methodology embraces formalized and non-formalized parts as a whole. Holonic and special convergent approaches are combined to ensure purposefulness and sustainability of collective decision-making. Inverse problem solving on topology spaces, control thermodynamics and non-formalizable (considering quantum and relativistic) semantics include observers of eigenforms of reality.
Findings
Collective decision-making cannot be represented only by formal means. Thus, this paper suggests the equation of hybrid reality (HyR), which integrates formalizable and non-formalizable parts conveying and coalescing holonic approaches, thermodynamic theory, cognitive modeling and inverse problem solving. The special convergent approach makes the solution of this equation purposeful and sustainable.
Research limitations/implications
The suggested approach is far reaching with respect of current state-of-the-art technology; medium-term limitations are expected in the creation of cognitive semantics.
Practical implications
Social-humanitarian events embrace all phenomena connected with individual and collective human behavior and decision-making. The paper will impact deeply networked experts, groups of crowds, rescue teams, researchers, professional communities, society and environment.
Originality/value
New possibilities for advanced AI to enable purposeful and sustainable social-humanitarian subjects. The special convergent information structuring during collective decision-making creates necessary conditions toward the goals.
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M. Iadh Ayari and Sabri T.M. Thabet
This paper aims to study qualitative properties and approximate solutions of a thermostat dynamics system with three-point boundary value conditions involving a nonsingular kernel…
Abstract
Purpose
This paper aims to study qualitative properties and approximate solutions of a thermostat dynamics system with three-point boundary value conditions involving a nonsingular kernel operator which is called Atangana-Baleanu-Caputo (ABC) derivative for the first time. The results of the existence and uniqueness of the solution for such a system are investigated with minimum hypotheses by employing Banach and Schauder's fixed point theorems. Furthermore, Ulam-Hyers
Design/methodology/approach
This paper considered theoretical and numerical methodologies.
Findings
This paper contains the following findings: (1) Thermostat fractional dynamics system is studied under ABC operator. (2) Qualitative properties such as existence, uniqueness and Ulam–Hyers–Rassias stability are established by fixed point theorems and nonlinear analysis topics. (3) Approximate solution of the problem is investigated by Adomain decomposition method. (4) Convergence analysis of ADM is proved. (5) Examples are provided to illustrate theoretical and numerical results. (6) Numerical results are compared with exact solution in tables and figures.
Originality/value
The novelty and contributions of this paper is to use a nonsingular kernel operator for the first time in order to study the qualitative properties and approximate solution of a thermostat dynamics system.
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The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is…
Abstract
Purpose
The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.
Design/methodology/approach
The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.
Findings
The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.
Originality/value
Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.
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