Affine Transformation-Enhanced Multifactorial Optimization for Heterogeneous Problems

Xue, Xiaoming; Zhang, Kai; Tan, Kay Chen; Feng, Liang; Wang, Jian; Chen, Guodong; Zhao, Xinggang; Zhang, Liming; Ye, Jun

doi:10.1109/tcyb.2020.3036393

Cited by 110 publications

(43 citation statements)

References 48 publications

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“…e evolutionary game theory is used to study the evolutionary stable strategy of tacit knowledge sharing between organizations [19]. Although these literature studies are based on bounded rationality, in general, they only considered the internal factors such as knowledge sources, knowledge characteristics, technical means, networks, and how external incentive policies affect the choice of network tacit knowledge sharing behaviors but they lack discussion [20][21][22][23].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Evolutionary Game Analysis of Knowledge Sharing in Low‐Carbon Innovation Network

Zheng

2021

Complexity

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Low-carbon technological innovation is the main means to develop a low-carbon economy, and network knowledge sharing and collaborative innovation is an effective model for the development of low-carbon technologies. First of all, this article adopts a decision-making experiment and evaluation laboratory method and interpretation structure model, combines the two methods, extracts the advantages of the two, and discards the shortcomings of the two, thus constructing a new optimized and upgraded interpretation structure model. We give methods to explore the main influencing factors of collaborative innovation of low-carbon technologies for online knowledge sharing. Based on the industrial network knowledge sharing and cooperation network environment, the network evolution game model of network knowledge sharing knowledge collaboration is constructed to study the rewards and punishments, the profit distribution rate, the knowledge potential difference, and the parameter pairing of the network knowledge sharing cooperation network structure in the process of network knowledge sharing and collaborative knowledge innovation. The influence of the network knowledge sharing cooperation strategy is obtained through simulation to change the size of the relevant parameters so that the network knowledge sharing cooperation agent chooses the network evolution game of the sharing strategy to realize the optimal evolutionary stable strategy. According to the simulation results, this article proposes suggestions from the following aspects, aiming to improve the overall knowledge synergy effect of the network knowledge sharing and cooperation network.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Evolutionary Game Analysis of Knowledge Sharing in Low‐Carbon Innovation Network

Zheng

2021

Complexity

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“…The spectrum with only rotational energy level transition, called a rotational spectrum, often occurs in the far-infrared and microwave region with a longer wavelength. In contrast, the spectrum with only electronic energy level transition often occurs in the ultraviolet or visible region [ 15 , 48 ].…”

Section: Diffusion Model Of Air Pollutantsmentioning

confidence: 99%

[Retracted] Analysis of Influencing Factors of PM2.5 Concentration and Design of a Pollutant Diffusion Model Based on an Artificial Neural Network in the Environment of the Internet of Vehicles

Pan

2021

Computational Intelligence and Neuroscience

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With the development of the automobile industry, artificial intelligence, big data, 5G, and other technologies, the Internet of Vehicles (IoV) industry has entered a stage of rapid development. In this paper, a pollutant diffusion model based on an artificial neural network is designed in the context of a vehicle network. The application of artificial neural networks in haze prediction is studied. This paper first analyzes the causes and influencing factors of haze and selects the most representative and relatively large meteorological factors from temperature, wind, relative humidity, and several pollutant factors. Through training and simulation, a haze prediction model in the Beijing, Tianjin, and Hebei regions of China is established. Finally, according to the collected meteorological data, the pollutant diffusion model is established. The model is deduced by a standard mathematical formula, which makes the prediction results more accurate and rigorous, and the main conclusions and feasible scientific suggestions are obtained. The simulation results show that the method is effective. By strengthening the service system of the IoV, meteorological services can be more intelligent, and the information acquisition and service ability of the vehicle network can be effectively improved.

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“…At stage 1, the weights for each existing layer of convolutional networks are initialized by applying the weights of the Convolutional Pose Machine and those layers at the rest of stage N (N > 1) are randomly initialized. The architecture is trained through backpropagation by using the Human 3.6 M dataset, which contains 3.6 million human poses and corresponding 3D pose information [85,86]. For the conversion from pixel belief maps into body joint localization, the pixel with the most confidence level is chosen as the location of each joint.…”

Section: Key Joints Extractionmentioning

confidence: 99%

Automatic Scaffolding Workface Assessment for Activity Analysis through Machine Learning

et al. 2021

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Scaffolding serves as one construction trade with high importance. However, scaffolding suffers from low productivity and high cost in Australia. Activity Analysis is a continuous procedure of assessing and improving the amount of time that craft workers spend on one single construction trade, which is a functional method for monitoring onsite operation and analyzing conditions causing delays or productivity decline. Workface assessment is an initial step for activity analysis to manually record the time that workers spend on each activity category. This paper proposes a method of automatic scaffolding workface assessment using a 2D video camera to capture scaffolding activities and the model of key joints and skeleton extraction, as well as machine learning classifiers, were used for activity classification. Additionally, a case study was conducted and showed that the proposed method is a feasible and practical way for automatic scaffolding workface assessment.

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Affine Transformation-Enhanced Multifactorial Optimization for Heterogeneous Problems

Cited by 110 publications

References 48 publications

[Retracted] Evolutionary Game Analysis of Knowledge Sharing in Low‐Carbon Innovation Network

[Retracted] Evolutionary Game Analysis of Knowledge Sharing in Low‐Carbon Innovation Network

[Retracted] Analysis of Influencing Factors of PM2.5 Concentration and Design of a Pollutant Diffusion Model Based on an Artificial Neural Network in the Environment of the Internet of Vehicles

Automatic Scaffolding Workface Assessment for Activity Analysis through Machine Learning

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