Search Results - (( using function mead algorithm ) OR ( sequence classification mining algorithm ))

Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

“…The performance of the proposed algorithm was tested on a set of seventeen well-known benchmark functions. …”
Get full text
Get full text
Get full text
Get full text

Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

Get full text
Get full text
Get full text

Data mining of protein sequences with amino acid position-based feature encoding technique by Iqbal, M.J., Faye, I., Md Said, A., Samir, B.B.

“…The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 classification accuracy over the Yeast protein sequence dataset. …”
Get full text
Get full text

A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

“…Conclusion: The proposed algorithm that utilized NMM is more functional to enhance the precision of localization because of particular characteristics that are the flexible implementation of NMM and the free cost of using the RSSI technique.…”
Get full text
Get full text
Get full text
Get full text

Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

“…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
Get full text
Get full text
Get full text

Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
Get full text
Get full text

Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

A review on data stream classification by A. A, Haneen, A., Noraziah, Abd Wahab, Mohd Helmy

“…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
Get full text
Get full text
Get full text

A Review on Data Stream Classification by A. A., Haneen, Noraziah, Ahmad, Mohd Helmy, Abd Wahab

“…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
Get full text
Get full text
Get full text

Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…Polarity classification or sentiment analysis is considered one of the opinion mining tasks which distinguishes between the polarities categories (two, three, and five) of opinions which focus on the degree of the sentiment (such as positive and negative for two polarities; and positive, neutral and negative for three polarities) that the text may contain. …”
Get full text
Get full text

Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm by Ling, Kuok Fong, Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
Get full text
Get full text
Get full text

Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
Get full text
Get full text
Get full text

Modelling transmission dynamics of Covid-19 during pre-vaccination period in Malaysia: a GUI-based seird predictive model using Streamlit by Norsyahidah Zulkarnain, Muhammad Salihi Abdul Hadi, Nurul Farahain Mohammad, Shogar, Ibrahim

“…The mathematical model is solved using the Scipy odeint function, which uses the Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. …”
Get full text
Get full text
Get full text

Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

“…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. …”
Get full text
Get full text

Modelling transmission dynamics of Covid-19 during pre-vaccination period in Malaysia : a gui-based seird predictive model using streamlit by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

“…The mathematical model is solved using the Scipy odeint function, which uses the Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. …”
Get full text
Get full text
Get full text

A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Sentiment analysis, also known as opinion mining, is a task that tries to automatically extract and classify sentiments conveyed in written content. …”
Get full text
Get full text

Simulation of COVID-19 outbreaks via graphical user interface (GUI) by Mohd Jamil, Norazaliza, Rosli, Norhayati, Muhammad, Noryanti

“…An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder- Mead algorithm and pattern-search technique. …”
Get full text
Get full text
Get full text

Mathematical model for predicting the performance of photovoltaic system with delayed solar irradiance by Siti Nurashiken, Md Sabudin

“…The numerical solution is obtained by adopting the Runge Kutta method coupled with a parameter fitting technique, the Nelder Mead algorithm, which is implemented by using MATLAB software. …”
Get full text
Get full text

Mathematical model for predicting the performance of photovoltaic system with delayed solar irradiance by Siti Nurashiken, Md Sabudin, Norazaliza, Mohd Jamil

“…The numerical solution is obtained by adopting the 4th-order Runge Kutta method coupled with a parameter fitting technique, the Nelder Mead algorithm, which is implemented by using MATLAB software. …”
Get full text
Get full text
Get full text