About this Research Topic
This Research Topic is part of the article collection series:
Volume I: Intelligent Computing Research with Applications in Ecological Plant Protection
Nowadays, with the development of Biotechnology, more and more Biotechnology research has been integrated into the research of Intelligent Computing. At the same time, with the development of Intelligent Computing, these technologies are also gradually feeding the research of Biotechnology. Evolutionary Computing, Swarm Intelligence, and other methods solve many practical problems by simulating animal predation, reproduction, and other behavior design algorithms. For example, Particle Swarm Optimization (PSO) algorithm is proposed by studying the behavior of bird predation. Ant Colony Optimization (ACO) algorithm was proposed by studying the bioinformatics principle of ant foraging route selection. Artificial Bee Colony (ABC) algorithm was proposed by studying the honey gathering behavior of bees. Genetic Algorithm (GA) was proposed by studying the principles of gene crossover and mutation. These algorithms are based on the results of bioinformatics theory, but they are mostly based on the biological behavior of animals. In addition, in the Internet of Things technology, a large number of sensors are used for the detection of ecological environment, biological growth environment, or animal behavior, but there are few instruments for the detection and evaluation of plant growth process and most of them play an auxiliary role. By studying these technologies, they are also able to promote the development of Biotechnology. For example, through Genetic Algorithm (GA) to guide the breeding and breeding of plants, through Swarm Intelligence to simulate the propagation process of plants for biological control, through sensors to control the environment and range of plants for the selection of breeding sites.
At present, bioinformatics has produced some integration with the field of Intelligent Computing, but the research field is mostly applied. This topic will mainly study the inspiration of Intelligent Computing from Biotechnology and the re-application of these enlightening research to Biotechnology. Contributions and comments on the latest research results on this topic are also welcome.
Potential topics may include, but are not limited to, the following:
• Swarm Intelligence algorithm guided by Biological Information
• Genetic Algorithm guided by plant propagation process
• Sensor design methods guided by Bioinformatics
• Biological control technology guided by swarm Intelligence Algorithm
• Plant mating techniques guided by Evolutionary Computation
• Biological culture technology guided by Sensor Network
Volume I: Intelligent Computing Research with Applications in Ecological Plant Protection
Nowadays, with the development of Biotechnology, more and more Biotechnology research has been integrated into the research of Intelligent Computing. At the same time, with the development of Intelligent Computing, these technologies are also gradually feeding the research of Biotechnology. Evolutionary Computing, Swarm Intelligence, and other methods solve many practical problems by simulating animal predation, reproduction, and other behavior design algorithms. For example, Particle Swarm Optimization (PSO) algorithm is proposed by studying the behavior of bird predation. Ant Colony Optimization (ACO) algorithm was proposed by studying the bioinformatics principle of ant foraging route selection. Artificial Bee Colony (ABC) algorithm was proposed by studying the honey gathering behavior of bees. Genetic Algorithm (GA) was proposed by studying the principles of gene crossover and mutation. These algorithms are based on the results of bioinformatics theory, but they are mostly based on the biological behavior of animals. In addition, in the Internet of Things technology, a large number of sensors are used for the detection of ecological environment, biological growth environment, or animal behavior, but there are few instruments for the detection and evaluation of plant growth process and most of them play an auxiliary role. By studying these technologies, they are also able to promote the development of Biotechnology. For example, through Genetic Algorithm (GA) to guide the breeding and breeding of plants, through Swarm Intelligence to simulate the propagation process of plants for biological control, through sensors to control the environment and range of plants for the selection of breeding sites.
At present, bioinformatics has produced some integration with the field of Intelligent Computing, but the research field is mostly applied. This topic will mainly study the inspiration of Intelligent Computing from Biotechnology and the re-application of these enlightening research to Biotechnology. Contributions and comments on the latest research results on this topic are also welcome.
Potential topics may include, but are not limited to, the following:
• Swarm Intelligence algorithm guided by Biological Information
• Genetic Algorithm guided by plant propagation process
• Sensor design methods guided by Bioinformatics
• Biological control technology guided by swarm Intelligence Algorithm
• Plant mating techniques guided by Evolutionary Computation
• Biological culture technology guided by Sensor Network
Keywords: Genetic Algorithm, Biotechnology, Internet of Things, Data Science, Intelligent Computing
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
