ArticleScientific reports2025
Research on location algorithm of opencast mine vehicle based on improved adaptive H ∞ CKF and IAGA.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aiming at the problems of non-line-of-sight delay and low positioning accuracy in the location of transport vehicles in the complex environment of the non-coal opencast mine, an improved adaptive H ∞ CKF and IAGA-TDOA positioning algorithm for transport vehicles in non-coal opencast mine is proposed, a Lora + 4G positioning platform is built, and the effectiveness of the algorithm is verified through simulation and field test. Improved Adaptive Genetic Algorithm (IAGA) updates the optimal preservation strategy of traditional genetic algorithm and redefines the adaptive cross rate and variation rate. The improved adaptive H ∞ Cubature Kalman Filter (CKF) algorithm reduces the effect of noise by weighting new and old noise. The simulation results show that the relative error of the improved adaptive H ∞ CKF algorithm is reduced by 85% compared with the traditional Kalman Filter. Comparing IAGA with other four algorithms to solve the TDOA positioning model, the IAGA algorithm has the smallest positioning error, and the minimum error is only 0.8 m. The field test shows that the average error of the system is within 7.4 m, and it can display the historical running track of the vehicle, which has a certain guiding significance for the automatic production of the mining area.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.