Search Results - intelligence based ((((mining algorithm) OR (search algorithm))) OR (scheduling algorithm))
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. …”
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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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A hybrid local search algorithm for minimum dominating set problems
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A hybrid local search algorithm for minimum dominating set problems
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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IP algorithms in compact rough classification modeling
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling
Published 2018“…The SDM is to make a division on the Swarm Intelligence (SI) algorithm which is to be a number of particles searching collections that properly can be regarded as divisions. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. 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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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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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications
Published 2024“…This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…This deficiency has prompted the need for a new intelligent data mining technique based on stochastic population-based optimization that could discover useful information from data. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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