Electric Vehicles (EV s) have become a necessary companion of humans in the last 5-6 years since these solely work on electricity. People are preferring EVs over regular vehicles since they are more energy efficient. ...
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Metaheuristic algorithms are widely used in the scientific community, with numerous algorithms inspired by various sources. Python programming language has become a valuable tool for implementing these algorithms in s...
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ISBN:
(纸本)9783031662676;9783031662683
Metaheuristic algorithms are widely used in the scientific community, with numerous algorithms inspired by various sources. Python programming language has become a valuable tool for implementing these algorithms in scientific research. This study uses the MEALPY Python open-source library to solve two constrained optimization problems from existing literature. The concept of the library is explained, and results for problems related to welded beam design and speed reducer designare obtained. Eight swarm-based algorithms from the library are selected for the comparative analysis. The results are compared and graphically presented in several figures. Discussion regarding the best fitness values, convergence, exploration and exploitation percentages, runtime, and trajectory of agents is made before concluding the study.
作者：
Garg, RuchiGulati, TarunMullana
Maharishi Markandeshwar Engineering College Department of Electronics and Communication Engineering Ambala India
Node localization is a requisite in wireless sensor networks (WSNs) because of their far-reaching applications in many fields like surveillance, tracking, security, etc. A major challenge for all these applications is...
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The proceedings contain 44 papers. The topics discussed include: joint beamforming design for reconfigurable intelligent surface assisted high-speed railway communication systems with per-antenna power constraints;pre...
ISBN:
(纸本)9781510682962
The proceedings contain 44 papers. The topics discussed include: joint beamforming design for reconfigurable intelligent surface assisted high-speed railway communication systems with per-antenna power constraints;prediction of short-wave maximum usable frequency by long short-term memory neural networks based on deep learning technique;research on system-of-systems simulation of space-earth integrated communication based on factor analysis;research on 2D beam scanning liquid crystal reflective array based on subarray division at K-band;study on the influence of different numbers of array elements on direction finding performance;and research on non-intrusive load identification technology.
Big data clustering on Spark is a practical method that makes use of Apache Spark's distributed computing capabilities to handle clustering tasks on massive datasets such as big data sets. Using the unsupervised l...
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Blockchain technology is playing a transformative role in reshaping how trust is established, information is shared transparently, and transactions are conducted efficiently. This research paper explores the current s...
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In this study, a fault diagnosis method combining the Pelican algorithm and BP neural network is proposed for improving the fault diagnosis accuracy and efficiency of microgrid systems. Pelican algorithm is a new opti...
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Area coverage is crucial for robotics applications such as cleaning, painting, exploration, and inspections. Hinged reconfigurable robots have been introduced for these application domains to improve the area coverage...
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ISBN:
(数字)9781665479271
ISBN:
(纸本)9781665479271
Area coverage is crucial for robotics applications such as cleaning, painting, exploration, and inspections. Hinged reconfigurable robots have been introduced for these application domains to improve the area coverage performance. However, the existing coverage algorithms of hinged reconfigurable robots require improvements in the aspects;consideration of beyond a limited set of reconfigurable shapes, coordinated reconfiguration and navigation, and online decision-making. Therefore, this paper proposes a novel online Complete Coverage Path Planning (CCPP) method for a hinged reconfigurable robot. The proposed CCPP method is designed with two sub-methods, the Global Coverage Path Planning (GCPP) and Local Coverage Path Planning (LCPP). The GCPP method has been implemented, adapting a Glasius Bio-inspired Neural Network (GBNN) that performs online path planning considering a fixed shape for the robot. Obstacle regions that the GCPP would not adequately cover due to access constraints are covered by the LCPP method that considers concurrent reconfiguration and navigation of the robot. A genetic algorithm determines the reconfiguration parameters that ascertain collision-free coverage and access of obstacle regions. Experimental results validate that the proposed online CCPP method is effective in ascertaining the complete area coverage in heterogeneous environments, including dynamic workspaces. Furthermore, the deployment of the LCPP method can considerably improve the coverage.
In cryptography, the design and implementation of sequence cryptography algorithms are challenging due to the complex structure of Non-Linear Boolean Function (NLBF) and limitations of available reconfigurable resourc...
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The proceedings contain 289 papers. The topics discussed include: employing multifaceted bioinformatics strategies for the discovery of novel ASK1 inhibitors targeting neurodegenerative disorders;sailfish optimizer al...
ISBN:
(纸本)9798350359688
The proceedings contain 289 papers. The topics discussed include: employing multifaceted bioinformatics strategies for the discovery of novel ASK1 inhibitors targeting neurodegenerative disorders;sailfish optimizer algorithm for effective toxic gas detection sensor placement in IioT;a comprehensive study on satellite-based data communication for big earth observation systems;APIs insight for phenotype classification and hive health forecasting using IoT and deep learning;the future of teaching: exploring the integration of machine learning in higher education;person recognition using ear images based on fractional gannet sparrow optimization enabled deep learning;restaurant recommendation system using machine learning algorithms;and AI-driven remote Parkinson's diagnosis with BPNN framework and cloud-based data security.
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