Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 20, 2025

This research utilizes time series models to forecast electricity generation from renewable energy sources and consumption. The configuration of optimal parameters for these typically requires optimization algorithms, but conventional algorithms may struggle with fixed search patterns limited robustness. To address this, we propose an auto-evolution hyper-heuristic algorithm named AE-GAPB. AE-GAPB integrates a genetic (GA) at the high-level component employs particle swarm (PSO) bat (BA) low-level component. GA continuously finds best hyperparameters PSO BA based on prediction accuracy, which significantly accelerates improves accuracy. Additionally, crossover mutation rates evolve over iteration fitness value space, further enhancing its adaptability. We validated six forecasting compared it five well-known as well GAPB without As result, achieved excellent results consumption datasets Hokkaido, Kyushu, Tohoku regions Japan.

Language: Английский

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Hybrid Optimization Model for Congestion-Free Multipath Routing and Load Balancing in IoT

Web Intelligence, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

The internet of things (IoT) has become popular as a means connecting people and in order to gather share data through embedded sensors. Consequently, robust multipath routing techniques are required guarantee network lifetime enhance energy efficiency. main challenge secure the longevity IoT networks is load balancing issue priority-based, congested-free communication infrastructure. This research intends propose IoT. steps carried out are: (i) routing, (ii) traffic scheduling. In route will be estimated via an optimization algorithm, termed hybrid dwarf mongoose-insisted pelican algorithm (HDMPOA) model which combination (POA) mongoose (DMO). done by considering parameters such message priority (improved computation) congestion control computation). Further, scheduling process HDMPOA under consideration balanced consumption collision rate. Finally, proposed suggested work evaluated over various methods using range metrics, priority, rate, control, latency, distance, throughput, so on. rate scheme-based for numbers round 20,000 approximately 5.2, minimal when compared existing techniques. scheme yielded higher 1.85 at 1500 (Node = 100) while conventional achieved rates.

Language: Английский

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Enhanced Fox Optimizer for Internet of Things Powered Personalized Healthcare Systems

International Journal of Communication Systems, Journal Year: 2025, Volume and Issue: 38(7)

Published: March 31, 2025

ABSTRACT The Internet of Things (IoT) paradigm has recently opened up new research opportunities in many academic and industrial fields, particularly medicine. IoT‐enabled technology transformed healthcare from a centralized model to personalized system driven by ubiquitous wearable devices smartphones. implementation IoT faces critical challenges, including energy efficiency, network reliability, task response time, availability services. An Adaptive Fox Optimizer (AFO) is proposed as novel IoT‐supported method for providing zero‐orientation nature AFO mitigated quasi‐oppositional learning. A reinitialization plan also presented improve exploration skills. Furthermore, an additional stage implemented with two movement techniques optimize search capabilities. In addition, multi‐best methodology used deviate the local optimum manage population more efficiently. Ultimately, greedy selection accelerates convergence exploitability. was rigorously evaluated, demonstrating significant improvements across key performance metrics. Compared conventional approaches, enhances 83.33%, reliability 11.32%, reduces consumption 19.12%, decreases times 25.14%. These results highlight AFO's ability resource allocation, enhance fault tolerance, prolong lifespan environments. By addressing this contributes developing efficient, reliable, responsive systems, paving way advancements health monitoring, telemedicine, smart hospital management.

Language: Английский

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Internet of Things Based Fuzzy Systems for Medical Applications: A Review

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 163883 - 163902

Published: Jan. 1, 2024

Language: Английский

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