Toward intelligent food drying: Integrating artificial intelligence into drying systems

Drying Technology, Journal Year: 2024, Volume and Issue: 42(8), P. 1240 - 1269

Published: May 24, 2024

Artificial intelligence (AI) and its data-driven counterpart, machine learning (ML), are rapidly evolving disciplines with increasing applications in modeling, simulation, control, optimization within the drying industry. This paper presents a comprehensive overview of progress made ML from shallow to deep implications for food drying. Theoretical foundations, advantages, limitations various approaches employed this domain explored. Additionally, advancements models, particularly those enhanced by algorithms, reviewed. The review underscores role intelligent configuration which affects their accuracy ability solve problems high energy consumption, nutrient degradation, uneven Drawing upon research achievements, integrating AI models real-time measuring methods is discussed, enabling dynamic determination optimal conditions parameter adjustments. integration facilitates automated decision-making, reducing human errors enhancing operational efficiency Moreover, demonstrate proficiency predicting times analyzing usage patterns, thereby minimize resource consumption while preserving product quality. Finally, identifies current obstacles technology development proposes novel avenues sustainable technologies.

Language: Английский

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Digital Analysis of Mycelium Growth and Mycelium Density In Vitro of Pleurotus ostreatus with Submerged Fermentation as Substrate Treatment

Mycobiology, Journal Year: 2025, Volume and Issue: 53(2), P. 214 - 224

Published: Feb. 13, 2025

Edible mushroom cultivation often involves sterilizing the substrate, or a similar heat process like pasteurization, to facilitate mycelial colonization. Chemical treatments are an alternative approach that is also employed in some regions. Mycelial growth and density were analyzed vitro by capturing daily photographs using digital camera, with sterilized substrate serving as control treatment. Our findings revealed both fermented substrates had patterns, although treatment required longer incubation time for full Mycelium denser structure compared treatment, reflecting interactions naturally-present microorganisms within substrate. Conversely, mycelium exhibited faster colonization times but less dense structure. Yeast bacterial colonies present throughout fermentation 7 days after P. ostreatus inoculation, indicating active microbial communities during An initial decrease CFU on 3rd day, followed increase 7th suggests shift toward anaerobic facultative due oxygen depletion fermentation. Mold disappeared end of Despite complex between yeast, bacteria, mycelium, appear have at least neutral effects, enabling growth.

Language: Английский

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An enhanced micro-PSO method to deal with asymmetric electricity markets competition within hydropower cascade

Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124235 - 124235

Published: Sept. 9, 2024

Language: Английский

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Dynamic Path Planning for Unmanned Surface Vehicles with a Modified Neuronal Genetic Algorithm

Applied System Innovation, Journal Year: 2023, Volume and Issue: 6(6), P. 109 - 109

Published: Nov. 14, 2023

Unmanned surface vehicles (USVs) are experiencing significant development across various fields due to extensive research, enabling these devices offer substantial benefits. One kind of research that has been developed produce better USVs is path planning. Despite numerous efforts employing conventional algorithms, deep reinforcement learning, and evolutionary USV planning consistently faces the challenge effectively addressing issues within dynamic environments where navigate. This study aims solve environmental problems, as well convergence problems in algorithms. proposes a neuronal genetic algorithm utilizes neural network input for processing with operator. The modifications this were implemented by incorporating partially exponential-based fitness function into algorithm. We also an inverse time variable function. These two faster convergence. Based on experimental results, which compared those basic neural-network-based proposed method can convergent solutions competitive performance total distance traveled both static environments.

Language: Английский

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Enhancing Accuracy of Metal Target Parameter Estimation Using Neural Networks

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 367 - 386

Published: Jan. 1, 2024

Language: Английский

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