ArticleComputational intelligence and neuroscience2022
Smart Home Product Layout Design Method Based on Real-Number Coding Genetic Algorithm.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Research on an intelligent fan cultural sustainability design method based on CPO-CNN-LSSVM.Scientific reports · 2025Article
- Optimization design of internal space layout of three-bedroom residential apartment based on IGA and DE algorithm.PloS one · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aiming at the problems of poor layout design efficiency of smart home products and low rationality of layout planning, a layout design method for smart home products based on a real-number coding genetic algorithm is proposed. The principles of smart home product layout design are analyzed and the smart home system architecture based on the Internet of Things is designed. Divide the combination of smart home product layout space according to spatial function, extract the visual features of smart home product layout, build a smart home product layout optimization model based on the two constraints of the total area and individual area of smart home product spatial layout, and design a real-coded genetic algorithm. The model is solved to improve the global convergence of the algorithm, and the optimization method for the layout of smart home products is obtained. The experimental results show that the layout design method of smart home products based on a real-number coding genetic algorithm can accurately extract the layout features of smart home products and accurately classify the number of pairs of homes. The efficiency of layout design and rationality of layout planning of smart home products are better, which reflects the effectiveness of this method.
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.