Data-Driven Optimization for Low-Carbon Prefabricated Components Production Based on Ant Colony Algorithms DOI Creative Commons
Chun-Ling Ho,

C. Wang,

Shenjun Qi

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(12), P. 4060 - 4060

Published: Dec. 21, 2024

The global industries are progressively transitioning towards low-carbon development; however, construction remains a significant contributor to energy consumption and carbon emissions. In promoting industrialized construction, the use of prefabricated buildings emerges as crucial strategy for achieving environmental sustainability. This study initially examines development current status concrete component factories in Fujian Province, focusing on regional distribution production conditions. It also gathers data emissions, time, costs formulate multi-objective optimization model. Utilizing ant colony algorithms, model aims minimize while adhering principles fostering sustainable buildings. results slabs indicate minimum cost RMB 5.7023 million, with associated emissions 1154.85 tons. Notably, variation 10,000 can lead maximum difference 50 tons emphasizing importance minimization primary objective. comparison conventional production, collaborative demonstrates reductions both Furthermore, when normal rush modes, be reduced by over 20%, resulting potential decrease up 50% Consequently, effectively mitigating is essential enhancing sustainability industry.

Language: Английский

Advanced Temporal Deep Learning Framework for Enhanced Predictive Modeling in Industrial Treatment Systems DOI Creative Commons

S Ramya,

S Srinath,

Pushpa Tuppad

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104158 - 104158

Published: Jan. 1, 2025

Language: Английский

Citations

0
FP-growth-based signature extraction and unknown variants of DoS/DDoS attack detection on real-time data stream DOI
Arpita Srivastava, Ditipriya Sinha

Journal of Information Security and Applications, Journal Year: 2025, Volume and Issue: 89, P. 103996 - 103996

Published: Feb. 7, 2025

Language: Английский

Citations

0
GA-PSO Algorithm for Microseismic Source Location DOI Creative Commons

Yaning Han,

Fanyu Zeng,

Fu Liu

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 1841 - 1841

Published: Feb. 11, 2025

Accurate source location is a critical component of microseismic monitoring and early warning systems. To improve the accuracy location, this manuscript proposes GA-PSO algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO). The enhances PSO by dynamically adjusting balance between global exploration local exploitation through sinusoidal function for nonlinear adjustment both learning factors, an adaptive inertia weight decreases quadratically iterations. Additionally, precision solutions further improved crossover mutation operations GA. In simulated model, demonstrated smallest error value, outperforming GA in terms accuracy. Furthermore, exhibited minimal sensitivity to wave speed fluctuations ±1%, ±3%, ±5%, maintaining within 0.5 m. validation blasting experiment at Shizhuyuan mine confirmed enhanced algorithm, 20.08 m, representing improvement 59% over 43% algorithm.

Language: Английский

Citations

0
NSGTO‐LSTM: Niche‐strategy‐based gorilla troops optimization and long short‐term memory network intrusion detection model DOI Creative Commons

Saritha Anchuri,

Arvind Ganesh,

Prathusha Perugu

et al.

ETRI Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

Abstract In recent decades, the rapid growth of Internet Things (IoT) has highlighted several network security problems. this study, an efficient intrusion detection (ID) system is implemented by using both machine learning and data mining concepts for detecting patterns. During initial phase, are collected from NSL‐KDD University New South Wales‐Network Based 15 (UNSW‐NB15) datasets. The then normalized/scaled employing a standard scaler technique. Next, informative feature values selected proposed optimization algorithm—that is, Niche‐Strategy‐based Gorilla Troops Optimization (NSGTO) algorithm. Finally, these transferred to Long Short‐Term Memory (LSTM) model classify types attacks on comparison existing ID systems, based NSGTO‐LSTM obtains classification accuracy 99.98% 99.90%

Language: Английский

Citations

0
The Random Neural Network – based Approach and Evolutionary Intelligence are integral components ofIOT – RNNEI, an intrusion detection system for IOT Networks DOI Creative Commons
Parisa Rahmani, Mohamad Arefi,

Seyyed Mohammad Saber SEYYED Shojae

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 12, 2024

Abstract Over the past few years, there has been significant research on Internet of Things (IOT), with a major challenge being network security and penetration. Security solutions require careful planning vigilance to safeguard system privacy. Adjusting weights neural networks shown improve detection accuracy some extent. In attack detection, primary goal is enhance precision using machine learning techniques. The paper details fresh approach for adjusting in random recognize attacks. Reviews method under consideration indicate better performance than methods, Nearest Neighbor, Support Vector Machine (SVM). Up 99.49% achieved while improved 99.01%. amalgamation most effective approaches these experiments through multi-learning model led an improvement 99.56%. proposed required less training time compared method.

Language: Английский

Citations

1
RNNEI: an attack detection model on Internet of Things Networks that utilizes Random Neural Networks and Evolutionary Intelligence DOI Creative Commons
Parisa Rahmani, Mohamad Arefi,

Seyyed Mohammad Saber SEYYED Shojae

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 29, 2024

Abstract Over the past few years, there has been significant research on Internet of Things (IOT), with a major challenge being network security and penetration. Security solutions require careful planning vigilance to safeguard system privacy. Adjusting weights neural networks shown improve detection accuracy some extent. In attack detection, primary goal is enhance precision using machine learning techniques. The paper details fresh approach for adjusting in random recognize attacks. Reviews method under consideration indicate better performance than methods, Nearest Neighbor, Support Vector Machine (SVM). Up 99.49% achieved while improved 99.01%. amalgamation most effective approaches these experiments through multi-learning model led an improvement 99.56%. proposed required less training time compared method.

Language: Английский

Citations

0
Data-Driven Optimization for Low-Carbon Prefabricated Components Production Based on Ant Colony Algorithms DOI Creative Commons
Chun-Ling Ho,

C. Wang,

Shenjun Qi

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(12), P. 4060 - 4060

Published: Dec. 21, 2024

The global industries are progressively transitioning towards low-carbon development; however, construction remains a significant contributor to energy consumption and carbon emissions. In promoting industrialized construction, the use of prefabricated buildings emerges as crucial strategy for achieving environmental sustainability. This study initially examines development current status concrete component factories in Fujian Province, focusing on regional distribution production conditions. It also gathers data emissions, time, costs formulate multi-objective optimization model. Utilizing ant colony algorithms, model aims minimize while adhering principles fostering sustainable buildings. results slabs indicate minimum cost RMB 5.7023 million, with associated emissions 1154.85 tons. Notably, variation 10,000 can lead maximum difference 50 tons emphasizing importance minimization primary objective. comparison conventional production, collaborative demonstrates reductions both Furthermore, when normal rush modes, be reduced by over 20%, resulting potential decrease up 50% Consequently, effectively mitigating is essential enhancing sustainability industry.

Language: Английский

Citations

0