Search Results - (( its application learning algorithm ) OR ( wave applications sensor algorithm ))*
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023text::Thesis -
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Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks
Published 2018“…To avert this problem, this study proposes a new mechanism called random traveling wave pulse-coupled oscillator algorithm, which is a self-organizing technique for energy-efficient wireless sensor networks using the phase-locking traveling wave pulse-coupled oscillator and random method on anti-phase of the pulse-coupled oscillator model. …”
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DESIGN AND DEVELOPMENT OF MULTI-INPUT SENSOR ALGORITHM FOR AUTONOMOUS UNDERWATER VEHICLE (AUV) APPLICATIONS
Published 2010“…This project is to design and develop a multi-input algorithm of sensors for Autonomous Underwater Vehicle (AUV) applications which is having high performance automated detection and monitoring on underwater application or for surveillances and defense application. …”
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Quasi linear algorithm for modelling shoreline change from AIRSAR/POLSAR polarized data
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Development of multi-input sensor algorithm for autonomous underwater vehicle (AUV) system stage 2
Published 2010“…This project is to develop a multi-input algorithm of sensors for Autonomous Underwater Vehicle (AUV) system for the stage two which is having high performance automated detection and monitoring on underwater application or for surveillances and defense application. …”
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A review of automatic driving target detection based on camera and millimeter wave radar fusion technology
Published 2025“…This review explores advancements in integrating these complementary sensors, focusing on state-of-the-art fusion methods, challenges, and applications. …”
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Firefly-inspired time synchronization mechanism for self-organizing energy efficient wireless sensor networks
Published 2017“…One major issue faced by Wireless Sensor Network (WSN), which is based on pulsecoupled oscillators (PCOs) is the energy consumption and loss of data due to the deafness, high packet collision and high power in the application. …”
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A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun
Published 2014“…This article demonstrated a miniature monopole antenna optimization at VHF band (30-300MHz) for FSR sensor application. Stub-loaded technique is applied in this design by placing the stub at strategic position along the antenna. 200MHz is targeted as operating frequency and antenna characteristic such as return loss, radiation patter, VSWR etc are targeted to be comparable to Commercial Off-The-Shelf (COTS) product. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Efficient data delivery in dense reader environment of passive sensor network
Published 2020“…The main objective of this research paper is to scrutinize the design of Wireless Surface Acoustic Wave (SAW) Sensor Network (WSSN). Passive SAW sensor is a ridged sensor which is best suited to monitor harsh environmental condition. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm
Published 2024“…Lattice-mismatched InGaAs has appeared to be emerging semiconductor materials for sensors and photovoltaic applications. The absorption coefficients of the materials are crucial in designing high-performance semiconductor devices. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
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