Search Results - (( developing objective optimization algorithm ) OR ( based application learning algorithm ))

A review of object detection in traffic scenes based on deep learning by Zhao, Ruixin, Tang, SaiHong, Supeni, Eris Elianddy, Abdul Rahim, Sharafiz, Fan, Luxin

“…This survey is based on the theory of deep learning. It systematically summarizes the Development and current research status of object detection algorithms, and compare the characteristics, advantages and disadvantages of the two types of algorithms. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

“…We report on the problem encoding, variation operators and different types of algorithms: Indicator Based Evolutionary Algorithm (IBEA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D) and Strength Pareto Evolutionary algorithm II (SPEA-II). …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…The objective is to develop an innovative and user-friendly platform offering accurate job position predictions to aid job seekers in finding optimal career opportunities. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”

Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

“…The main objective of an object-oriented application framework is to promote the reuse of both design and code in the development of new applications. …”

Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…Wavelet networks (WNs) have been introduced as an alternative method of the neural networks for nonlinear system identification and used with model predictive control (MPC) techniques in many applications. Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

“…Based on the findings, the development of the new systematic SAT and the implementation of the Hybrid Black Hole algorithm to optimize the retrieval capabilities of DHNN to achieve multi-objective functions result in updated final neuron states with high diversity, high attainment of global minima solutions, and produces states with a low similarity index. …”
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Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

“…The three main objectives are: (i) to develop a malware RGB image-based dataset and classifier using a parallel CNN (PCNN), (ii) to develop an enhanced parallel deep learning (EPDL) model for malware detection (MD) and build a response system (RS) by applying PCNN, and (iii) to evaluate the developed model with previous studies based on the accuracy rate. …”

Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…Thereafter, the Multi-Leader Particle Swarm Optimization algorithm (MLPSO), which is a novel evolutionary optimization technique in the field of power systems was developed and employed in the optimization process. …”

Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nurul Amira, Mhd Rizal, Nor Maniha, Abd Ghani, Mohd Falfazli, Mat Jusof, Mohd Ashraf, Ahmad

“…This paper presents an improved version of Manta Ray Foraging Optimization (MRFO). MRFO is relatively a single objective optimization algorithm. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

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Comparative Analysis of Peak Current Prediction based on Random Forest and MLP Neural Network Algorithms by Bhoyar P., Rahman M.S.A., Irfan S.A., Amirulddin U.A.U.