A new mycorrhized tree optimization nature-inspired algorithm

Carreon-Ortiz, Hector; Valdez, Fevrier

doi:10.1007/s00500-022-06865-8

Cited by 7 publications

(2 citation statements)

References 36 publications

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“…Chemicals released by plants warn other plants to produce distasteful chemicals to deter grazing animals in a similar way [ 82 , 83 , 84 , 85 ]. Recently there have been multiple accounts in both peer reviewed journals and in the popular press about the so-called “wood-wide web” [ 86 , 87 , 88 ], detailing the complex way trees communicate using mycelium as a conduit to carry information between tree roots.…”

Section: Chemical Ecology Mychorrysal and Microbiome Evidencementioning

confidence: 99%

“…This could include time, dose, system level and outcome as initial parameters and build on this to include other determinants of outcome as they were identified. Such an approach is used by Carreon-Ortiz, & Valdez cited above [ 86 ], A key feature of the model which we have called the variable response model (VRM) would be its emphasis on outcome or response not as a surrogate for dose but as the starting point of interest. We propose the use of the term infosome rather than infochemicals to highlight the fact that radiation-induced communication signals include physical as well as chemical agents.…”

Section: A Way Forward? the Variable Response Modelmentioning

confidence: 99%

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Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

Mothersill

Cocchetto

Seymour

2022

IJMS

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The role of signalling in initiating and perpetuating effects triggered by deposition of ionising radiation energy in parts of a system is very clear. Less clear are the very early steps involved in converting energy to chemical and biological effects in non-targeted parts of the system. The paper aims to present a new model, which could aid our understanding of the role of low dose effects in determining ultimate disease outcomes. We propose a key role for electromagnetic signals resulting from physico-chemical processes such as excitation decay, and acoustic waves. These lead to the initiation of damage response pathways such as elevation of reactive oxygen species and membrane associated changes in key ion channels. Critically, these signalling pathways allow coordination of responses across system levels. For example, depending on how these perturbations are transduced, adverse or beneficial outcomes may predominate. We suggest that by appreciating the importance of signalling and communication between multiple levels of organisation, a unified theory could emerge. This would allow the development of models incorporating time, space and system level to position data in appropriate areas of a multidimensional domain. We propose the use of the term “infosome” to capture the nature of radiation-induced communication systems which include physical as well as chemical signals. We have named our model “the variable response model” or “VRM” which allows for multiple outcomes following exposure to low doses or to signals from low dose irradiated cells, tissues or organisms. We suggest that the use of both dose and infosome in radiation protection might open up new conceptual avenues that could allow intrinsic uncertainty to be embraced within a holistic protection framework.

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Section: Chemical Ecology Mychorrysal and Microbiome Evidencementioning

confidence: 99%

Section: A Way Forward? the Variable Response Modelmentioning

confidence: 99%

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

Mothersill

Cocchetto

Seymour

2022

IJMS

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CMOA—Continuous Mycorrhiza Optimization Algorithm

Valdez,

Carreon-Ortiz,

Castillo

2023

SpringerBriefs in Applied Sciences and Technology

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Learning search algorithm: framework and comprehensive performance for solving optimization problems

Qu,

Peng,

Zeng

2024

Artif Intell Rev

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In this study, the Learning Search Algorithm (LSA) is introduced as an innovative optimization algorithm that draws inspiration from swarm intelligence principles and mimics the social learning behavior observed in humans. The LSA algorithm optimizes the search process by integrating historical experience and real-time social information, enabling it to effectively navigate complex problem spaces. By doing so, it enhances its global development capability and provides efficient solutions to challenging optimization tasks. Additionally, the algorithm improves the collective learning capacity by incorporating teaching and active learning behaviors within the population, leading to improved local development capabilities. Furthermore, a dynamic adaptive control factor is utilized to regulate the algorithm’s global exploration and local development abilities. The proposed algorithm is rigorously evaluated using 40 benchmark test functions from IEEE CEC 2014 and CEC 2020, and compared against nine established evolutionary algorithms as well as 11 recently improved algorithms. The experimental results demonstrate the superiority of the LSA algorithm, as it achieves the top rank in the Friedman rank-sum test, highlighting its power and competitiveness. Moreover, the LSA algorithm is successfully applied to solve six real-world engineering problems and 15 UCI datasets of feature selection problems, showcasing its significant advantages and potential for practical applications in engineering problems and feature selection problems.

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A new mycorrhized tree optimization nature-inspired algorithm

Cited by 7 publications

References 36 publications

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

Low Dose and Non-Targeted Radiation Effects in Environmental Protection and Medicine—A New Model Focusing on Electromagnetic Signaling

CMOA—Continuous Mycorrhiza Optimization Algorithm

Learning search algorithm: framework and comprehensive performance for solving optimization problems

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