Search Results - (( intelligence based gene algorithm ) OR ( intelligence based generic algorithm ))
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The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. The user participates in the search by proposing a new individual. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…Then, in order to cope with the limitations of the existing artificial intelligence (AI) based methods, optimized gene expression programming (GEP) is applied to precisely formulate the relationships between historical data and EEC of ASEAN-5 countries. …”
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Optic cup and optic disc segmentation using improved selfish gene algorithm / Norharyati Md Ariff
Published 2016“…This study performed using a new bio-inspired algorithm; Selfish Gene Algorithm (SFGA) for optic cup and optic disc segmentation. …”
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Adapting robot kinematics for human-arm motion recognition
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A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli
Published 2023“…Ant colony optimization (ACO) is a swarm intelligent optimization that is inspired based on the natural foraging behavior of ant colony. …”
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A technical perspective on integrating artificial intelligence to solid‑state welding
Published 2024“…Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes with an accuracy range of 85 – 99%, while Response Surface Methodology such as Optimization Strategy can achieve up to 95 percent confidence levels in improving bonding strength and optimizing process parameters. …”
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A technical perspective on integrating artificial intelligence to solid‑state welding
Published 2024“…Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes with an accuracy range of 85 – 99%, while Response Surface Methodology such as Optimization Strategy can achieve up to 95 percent confidence levels in improving bonding strength and optimizing process parameters. …”
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Speech emotion verification system (SEVS) based on MFCC for real time applications
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…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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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm
Published 2024“…By selecting the best gene for the next iteration, the utilization of Genetic Algorithm has significantly reduced the number of iterations from a maximum of 10 000 to 300. …”
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