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Sales prediction for media platforms advertising expenditure using Linear Regression / Nur Athirah Abdurahman by Abdurahman, Nur Athirah

“…The study focuses on the application of the Linear Regression algorithm to predict sales outcomes based on advertising spending patterns. …”
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Efficient dynamic DNA-based block cipher algorithm by Chng, Chern Wei

“…The use of non-linear S-Box is essential in preventing linear approximations that could lead to successful attacks, such as differential cryptanalysis. …”
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Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

“…This research will first make use of the matrix determinants properties, linear equations and its inverses, identifies the similarity elements and combines them with irreducible polynomials and affine transformation to produce new determinants-boxes to be used in the substitution layer. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach by Gholizadeh, Somayyeh

“…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Combination of linear and gradient vector flow field digital mosaic rendering for automated tile placement by Akindokun, Tolulope John

“…Firstly, an improved algorithm using hybrid GVF digital mosaic rendering. …”
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda by Mohamad @ Hamza, Mohd. Azwan

“…Recently, Fuzzy Logic is used to determine and classify the discourse element while Stepwise Linear Regression Algorithm (SLR) is used to make closest prediction for style of writing. …”
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A NOVEL FORWARD BACKWARD LINEAR PREDICTION ALGORITHM FOR SHORT TERM POWER LOAD FORECAST by BAHARUDIN, ZUHAIRI

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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

“…This complex problem has a cubic non-linear objective function. Comprehensive solutions to a non-linear real world objective function are achieved thus establishing the usefulness of the realistic membership function for decision making in industrial production planning. …”
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Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach by Farid, Mazen, Heng, Siong Lim, Chin, Poo Lee, Latip, Rohaya

“…We compare our proposed method to five distinct decision-making procedures using common scientific workflows with competing objectives: Pareto dominance, multi-criteria decision-making (MCDM), linear normalization I, linear normalization II, and weighted aggregated sum product assessment (WASPAS). …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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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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Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model by Ahmad, Mohd Ashraf

“…In the Hammerstein model identification a continuoustime linear system is used and the hMVOSCA based method is used to tune the coefficients of both the Hammerstein model subsystems (linear and nonlinear) such that the error between the estimated output and the actual output is reduced. …”
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AI recommendation penetration testing tool for SQL injection: linear regression by Ahmad Fuad, Norshahira Elliyana, Saad, Shahadan

“…This project, Extreme programming methodology was used to construct the flow of the project. To make sure this project going smoothly many hardware and software were used, such as Django, Nginx, VMware and many more. …”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

“…This study uses the genetic algorithm radial basis, neural network model, to make judgments on the relationships contained in this sequence and compare and analyze the prediction effect and generalization ability of the model to verify the applicability of the genetic algorithm radial basis, neural network model, based on the modeling of historical data, which may contain linear and nonlinear relationships by itself, so this study uses the genetic algorithm radial basis, neural network model, to make, compare, and analyze judgments on the relationships contained in this sequence.…”
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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Lai, Fong Woon

“…Financial data is characterized as non-linear, chaotic in nature and volatile thus making the process of forecasting cumbersome. …”
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Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

“…In existing research, many problems involving scheduling have been solved by using genetic algorithm method. There are many other methods that were also being used such as linear programming, integer linear programming, tabu search, ant colony optimization (ACO) algorithm and goal programming. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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