A novel dynamic weight allocation method for multisource information fusion

Li, Yuting; Xiao, Fuyuan

doi:10.1002/int.22318

Cited by 5 publications

(5 citation statements)

References 60 publications

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“…This could be solved by coupling a knowledge model of crop growth 50 containing the environment and suitable cultivar information. Given ecological, physical, and economic information, different weights can be allocated in building the constraints 51 …”

Section: Discussionmentioning

confidence: 99%

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Parallel crop planning based on price forecast

Fan

Kang

Wang

et al. 2021

Int J of Intelligent Sys

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Agrifood system actors operate within diverse sociocultural, economic, and biophysical settings. For growers, crop planning, usually a yearly business plan, is a key decision to make on when, what, and how many to plant. It is a challenging task as it deals with multiple constraints in volatile economic and/or climate environment. Most crop planning models have difficulty in adapting to changing situation. In this study, a parallel system of crop planning composed of the artificial system, computational experiment, and parallel execution is proposed. The farmers are described as agents, and the decision is made based on the heuristic searching of optimal plan; the adaption of plan is triggered autonomously given strong environment changes. Focus is given to economic environment, which is indicated as product price. In a case study, the economic environment of the artificial system is built based on the monthly and weekly price information for 13 products during 7 years. The computational experiment provides the initial cropping plan and harvest time, with social and ecological constraints. Result shows that the cropping plan can further adapt to price variation. This flexible cropping plan system can strengthen the capability of cooperatives serving small-scale farmers.

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Section: Discussionmentioning

confidence: 99%

“…Given ecological, physical, and economic information, different weights can be allocated in building the constraints. 51…”

Section: Comparison On a Descriptive Modelmentioning

confidence: 99%

Parallel crop planning based on price forecast

Fan

Kang

Wang

et al. 2021

Int J of Intelligent Sys

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“…To achieve dynamic correlation between fusion results and fusion process, inspired by references [4,33,34], the GIQ calculation method as adapted and introduced into the fusion algorithm proposed in this paper, to achieve dynamic information weighting during adjacent sensor information interaction. By calculating the bias of the local fusion results of the sensors at each moment, they are converted into dynamic information weights for information interaction ω ij (k).…”

Section: Multi-source Information Fusion Algorithm With Finite-time C...mentioning

confidence: 99%

“…The important content of sensor networks research is the state estimation of filter output. Common information fusion algorithms applied to state estimation in multi-sensor networks including weighted averaging [4,5], multi-Bayesian estimation methods [6,7], Kalman filtering (KF) [8,9].…”

Section: Introduction 1motivation and Related Workmentioning

confidence: 99%

Optimal Distributed Finite-Time Fusion Method for Multi-Sensor Networks under Dynamic Communication Weight

Yu,

Dai,

et al. 2023

Sensors

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Aiming at the problem of distributed state estimation in sensor networks, a novel optimal distributed finite-time fusion filtering method based on dynamic communication weights has been developed. To tackle the fusion errors caused by incomplete node information in distributed sensor networks, the concept of limited iterations of global information aggregation was introduced, namely, fast finite-time convergence techniques. Firstly, a local filtering algorithm architecture was constructed to achieve fusion error convergence within a limited number of iterations. The maximum number of iterations was derived to be the diameter of the communication topology graph in the sensor network. Based on this, the matrix weight fusion was used to combine the local filtering results, thereby achieving optimal estimation in terms of minimum variance. Next, by introducing the generalized information quality (GIQ) calculation method and associating it with the local fusion result bias, the relative communication weights were obtained and embedded in the fusion algorithm. Finally, the effectiveness and feasibility of the proposed algorithm were validated through numerical simulations and experimental tests.

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“…According to recent studies, the performance of fusion methods may be limited when decision conflict occurs (Deng et al, 2016;Li and Xiao, 2021). Large differences in classification performances between the two heterogeneous information sources may lead to decision conflicts.…”

Section: Performance Of Dynamic Probability Integration In Conflict A...mentioning

confidence: 99%

Dynamic probability integration for electroencephalography-based rapid serial visual presentation performance enhancement: Application in nighttime vehicle detection

Cui

Xie

et al. 2022

Front. Comput. Neurosci.

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BackgroundRapid serial visual presentation (RSVP) has become a popular target detection method by decoding electroencephalography (EEG) signals, owing to its sensitivity and effectiveness. Most current research on EEG-based RSVP tasks focused on feature extraction algorithms developed to deal with the non-stationarity and low signal-to-noise ratio (SNR) of EEG signals. However, these algorithms cannot handle the problem of no event-related potentials (ERP) component or miniature ERP components caused by the attention lapses of human vision in abnormal conditions. The fusion of human-computer vision can obtain complementary information, making it a promising way to become an efficient and general way to detect objects, especially in attention lapses.MethodsDynamic probability integration (DPI) was proposed in this study to fuse human vision and computer vision. A novel basic probability assignment (BPA) method was included, which can fully consider the classification capabilities of different heterogeneous information sources for targets and non-targets and constructs the detection performance model for the weight generation based on classification capabilities. Furthermore, a spatial-temporal hybrid common spatial pattern-principal component analysis (STHCP) algorithm was designed to decode EEG signals in the RSVP task. It is a simple and effective method of distinguishing target and non-target using spatial-temporal features.ResultsA nighttime vehicle detection based on the RSVP task was performed to evaluate the performance of DPI and STHCP, which is one of the conditions of attention lapses because of its decrease in visual information. The average AUC of DPI was 0.912 ± 0.041 and increased by 11.5, 5.2, 3.4, and 1.7% compared with human vision, computer vision, naive Bayesian fusion, and dynamic belief fusion (DBF), respectively. A higher average balanced accuracy of 0.845 ± 0.052 was also achieved using DPI, representing that DPI has the balanced detection capacity of target and non-target. Moreover, STHCP obtained the highest AUC of 0.818 ± 0.06 compared with the other two baseline methods and increased by 15.4 and 23.4%.ConclusionExperimental results indicated that the average AUC and balanced accuracy of the proposed fusion method were higher than individual detection methods used for fusion, as well as two excellent fusion methods. It is a promising way to improve detection performance in RSVP tasks, even in abnormal conditions.

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A novel dynamic weight allocation method for multisource information fusion

Cited by 5 publications

References 60 publications

Parallel crop planning based on price forecast

Parallel crop planning based on price forecast

Optimal Distributed Finite-Time Fusion Method for Multi-Sensor Networks under Dynamic Communication Weight

Dynamic probability integration for electroencephalography-based rapid serial visual presentation performance enhancement: Application in nighttime vehicle detection

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