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Titlebook: Complex, Intelligent, and Software Intensive Systems; Proceedings of the 1 Leonard Barolli,Farookh Khadeer Hussain,Makoto Ike Conference pr

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樓主: DIGN
31#
發(fā)表于 2025-3-26 22:04:10 | 只看該作者
32#
發(fā)表于 2025-3-27 03:56:37 | 只看該作者
IoT Node Selection and Placement: A New Approach Based on Fuzzy Logic and Genetic Algorithmthe performance of the proposed system by a simulation scenario. For the IoT node fuzzy-based selection system, we show that the system makes a proper selection of IoT nodes. The simulation results of GA-based system show that the constructed network, can cover both events.
33#
發(fā)表于 2025-3-27 07:28:25 | 只看該作者
34#
發(fā)表于 2025-3-27 10:27:17 | 只看該作者
35#
發(fā)表于 2025-3-27 16:10:49 | 只看該作者
Message Ordering Based on the Object-Based-Causally (OBC) Precedent Relation . and . are related in terms of topics. In this paper, we propose an MTBC (Modified Topic-Based Causally ordering) protocol which uses topic vectors. In the evaluation, we show clear how many number of messages are unnecessarily ordered in the MTBC protocol.
36#
發(fā)表于 2025-3-27 20:00:29 | 只看該作者
A Comparative Analysis of Neural Networks and Enhancement of ELM for Short Term Load Forecastings. XGboost and decision tree are used for features importance calculation and RFE is used for features extraction on the basis of score assigned. Three basic techniques (CNN, MLP and ELM) are used for forecasting. Furthermore, ELM is enhanced and E_ELM is proposed for STLF. Moreover, results are eva
37#
發(fā)表于 2025-3-28 01:59:33 | 只看該作者
2194-5357 ns provide a fruitful impulse for both software intensive systems and complex systems. Research in the field of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences is a 978-3-030-22353-3978-3-030-22354-0Series ISSN 2194-5357 Series E-ISSN 2194-5365
38#
發(fā)表于 2025-3-28 03:02:56 | 只看該作者
39#
發(fā)表于 2025-3-28 06:49:59 | 只看該作者
Performance Analysis of WMNs by WMN-PSOHC-DGA Simulation System Considering Random Inertia Weight an high speed wireless Internet connectivity. In our previous work, we implemented a Particle Swarm Optimization (PSO) and Hill Climbing (HC) based hybrid simulation system, called WMN-PSOHC, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in
40#
發(fā)表于 2025-3-28 12:39:37 | 只看該作者
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