Search Results - machine ((means algorithm) OR (based algorithm))

Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Specifically, the PSO algorithm achieved a mean surface roughness improvement of 0.44% over GA, and 1.1% and 1.23% over ACO and FA, respectively. …”
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Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

“…This study assesses the performance of each hybrid algorithms based on three statistical indices viz. Mean Square Error (MSE), Root Mean Square Percentage Error (RMSPE) and Theil’s U which is realized on raw and normalized data set. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem by Abdelraheem Elhaj, Hazir Farouk

“…This means that it is highly unlikely to find a polynomial algorithm to solve the problem. …”
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Towards the utilization of normalized LMS algorithm in adaptive filter by Misbah Emhammed, Misbah Abdelsalam, Ho, Yih Hwa

“…In this paper, we focused on how the development of algorithms helped reduce the level of noise. This in turn led us to utilize the Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms in order to do so. …”
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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

“…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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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations by Nouri, Hossein, Tang, Sai Hong

“…This paper investigates the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem. In addition, for this purpose matrix-based bacteria foraging optimization algorithm traced constraints handling (MBATCH) is developed. …”
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

Subjects: “…Algorithms…”

Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

“…The idea behind the adaptive job scheduling algorithm is the hybrid algorithms that consist of Ant Colony Optimization (ACO) and Tabu algorithms. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

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An efficient VM scheduling algorithm to minimize the makespan and maximize the profit by Ibrahim, Aws Fadhil

“…The second process is hyper analytical task scheduling algorithm, and based on the scheduled task, the policy based profit maximization algorithm was proposed in final process. …”
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Cost-based hybrid flow shop scheduling with uniform machine optimization using an improved tiki-taka algorithm by Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…The cost-based HFSS model and TTA algorithm have been tested using benchmark and case study problems. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

“…The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.