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ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Advanced solar tracking system with temperature control and real-time monitoring by Mahmuddin, Shohibul Syahmi, Nordin, Siti Aminah, Azli, Shakira Azeehan, Mohamad, Nurul Nadia

“…The system integrates key components such as a humidity sensor, light-dependent resistor (LDR) sensor, servo motor, relay module, and LCD display, working in unison to optimize solar panel performance. …”
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Arduino solar tracker with blynk / Muhammad Azim Hafizi Azlan by Azlan, Muhammad Azim Hafizi

“…The system maximizes solar energy capture by ensuring correct panel alignment in real-time through the use of servo motors, light sensors, and an intelligent algorithm. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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Optimal dynamic reconfiguration of large-scale PV plant under partial shading conditions based on two reconfigurable stages by Ajmal A.M., Ramachandaramurthy V.K., Tomar A., Ekanayake J.B.

Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

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Severity Estimation of Plant Leaf Diseases Using Segmentation Method by Chyntia Jaby, Entuni, Tengku Mohd Afendi, Zulcaffle, Kuryati, Kipli, Fatih, Kurugollu

“…The best severity estimation algorithm and color space used to estimate the diseases severity of plant leaf is the combination of Fuzzy C-Means and YCbCr color space. …”
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On time-domain OFDM channel estimation: Use of pilots correlation for digital video broadcasting (DVB) cable receiver by Khan, A.M., Jeoti, V.

“…In this paper, an improved OFDM time domain channel estimation algorithm is proposed for (DVB) Cable receivers. …”
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MIMO OFDM channel estimation based on RLS algorithm: the time- versus frequency-domain implementations by Hezam, Mohammed Abdo Saeed, Mohd Ali, Borhanuddin, Khatun, Sabira, Noordin, Nor Kamariah, Ismail, Mahamod

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Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…In the first sub-algorithm, the state mean propagation removes the Gaussian white noise to obtain the expected solution. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

“…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
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Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system by Abdolee, Reza

“…At the next stage of the project, the effect of channel estimation algorithm on performance of MIMO-OFDM system was investigated. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian by Ng, Tarng Jian

“…The study addresses challenges posed by signal fluctuations, non-line-of-sight propagation, and the need for continuous positioning estimation in dynamic environments. Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
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