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  1. 1
    An Improved Spiral Dynamic Optimization Algorithm with Engineering Application

    An Improved Spiral Dynamic Optimization Algorithm with Engineering Application by Ahmad Nor Kasruddin, Nasir, Tokhi, M. O.

    Published 2015
    “…This paper presents the development of an improved spiral dynamic optimization algorithm with application to nonparametric fuzzy logic modeling of a twin rotor system (TRS). …”
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  2. 2
    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…The system identification results show the effectiveness of the proposed algorithm for nonparametric model development.…”
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  3. 3
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.…”
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  4. 4
    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…Data arrives from operational field in a stream model and similarity-based classification algorithms must identify them with acceptable performance. …”
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  5. 5
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  6. 6
    Reservoir Operation Analysis Aimed to Optimize the Capacity Factor of Hydroelectric Power Generation

    Reservoir Operation Analysis Aimed to Optimize the Capacity Factor of Hydroelectric Power Generation by Asfaw, Tilahun Derib, Hashim, Ahmad Mustafa

    Published 2011
    “…The test results indicated that there is no trend in the generation of electricity. Optimal turbine release was found through genetic algorithm optimization model. …”
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  7. 7
    Reservoir Operation Analysis Aimed to Optimize the Capacity Factor of Hydroelectric Power Generation

    Reservoir Operation Analysis Aimed to Optimize the Capacity Factor of Hydroelectric Power Generation by Asfaw, Tilahun Derib, Hashim, Ahmad Mustafa

    Published 2011
    “…The test results indicated that there is no trend in the generation of electricity. Optimal turbine release was found through genetic algorithm optimization model. …”
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  8. 8
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  9. 9
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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  10. 10
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  11. 11
    Hybrid performance measures and mixed evaluation method for data classification problems

    Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

    Published 2012
    “…Moreover, the GA model that was optimized by OAERP2 measure (GAoe2) performed significantly and statistically differently as compared to other OAERP2-based models through win-draw-loss evaluation method and two nonparametric tests. …”
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  12. 12
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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  13. 13
    Hybrid pitch angle controller approaches for stable wind turbine power under variablewind speed

    Hybrid pitch angle controller approaches for stable wind turbine power under variablewind speed by Sarkar, M.R., Julai, S., Tong, C.W., Uddin, M., Romlie, M.F., Shafiullah, G.M.

    Published 2020
    “…In addition, ant colony optimization (ACO), particle swarm optimization (PSO), and classical Ziegler-Nichols (Z-N) algorithms have been used for tuning the PID controller parameters to obtain within rated stable output power of WTs from fluctuating wind speeds. …”
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  14. 14
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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