Search Results - (( java application mining algorithm ) OR ( parameter adoption case algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Addressing this issue, this paper proposes the adoption of parameter free optimization algorithms as the basis of future t-way strategies. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive systems, such an assumption is invalid as some parameter operations, or events, occur in sequence and hence, creating a possibility of bugs or faults triggered by the order, or sequence, of input parameters. …”
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One Parameter at a time Combinatorial Testing Strategy Based on Harmony Search Algorithm OPAT-HS by Al-Sewari, Abdul Rahman Ahmed Mohammed, Mu’aza, Aminu Aminu, Rassem, Taha H., Tairan, Nasser M., Shah, Habib, Kamal Z., Zamli

“…Even though there are some existing optimization algorithm based combinatorial testing strategies, that minimize the number of test cases, but most of these strategies based on one-test-at-a-time (OTAT) approach and none of them has adopted the one-parameter-at-a-time (OPAT) approach. …”
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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. …”
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An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

“…Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. In the case of reactive system, such an assumption is invalid as some parameter operations (or events) occur in sequence and hence, creating a possibility of bugs triggered by the order (or sequence) of input parameters. …”
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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

“…However, among the adopted MHAs, not all are compatible with optimizing the ANN for streamflow forecasting, thus requiring a thorough study as performance varies from case to case. …”

Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Assessing the chaotic map population initializations for sine cosine algorithm using the case study of pairwise test suite generation by Din, Fakhrud, Kamal Zuhairi, Zamli, Abdullah, Nasser

“…The main strength of SCA is its simplicity and straightforward implementation as well as provides no parameter control adjustment. For these reasons, SCA can be adopted in many optimization problems quickly and without much tuning. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing by Muazu, A.A., Hashim, A.S., Sarlan, A.

“…This research paper outlines hundred and ten (110) outstanding nature-inspired metaheuristic algorithms for the last decades (2001 and 2021) such as Coronavirus Optimization Algorithm, Ebola Optimization Algorithm, Harmony Search, Tiki-Taka Algorithm, and so on. …”
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Combinatorial test suites generation strategy utilizing the whale optimization algorithm by Ali Abdullah, Hassan, Salwani, Abdullah, Kamal Zuhairi, Zamli, Rozilawati, Razali

“…To address this issue, combinatorial t-way testing (where t indicates the interaction strength, i.e. the number of interacting parameters (input)) was adopted to minimize the number of cases for testing. …”
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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Yahaya, Muhammad Sabo, Hashim, Ahmad Sobri B., Oluwagbemiga Balogun, Abdullateef, Aminu Muazu, Aminu, Sabo Usman, Fatima, Adamu Aliyu, Dahiru, Uwaisu Muhammad, Abdullahi

“…This review systematically examines the role of metaheuristic algorithms in pairwise test case generation, focusing on their exploration and exploitation mechanisms to address local optima challenges. …”
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Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

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