Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector. Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art algorithms perform using one or two performance indicators without clear evidence or justification of the efficiency of these indicators over others. Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. The study followed a systematic procedure to analyze 49 evaluation criteria, sub-criteria, and its performance indicators, a penal of 23 domain experts, participated in this study. Lastly, the most suitable criteria outcomes are formulated in the unifying model and evaluate by experts to verify the appropriateness and suitability of the model in assessing the MaOO algorithms fairly and effectively.
The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength. As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a
... Show MoreThis article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f
... Show MoreWith its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
... Show MoreMixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.
Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.
to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure
... Show MoreBackground: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost
... Show MoreBackground: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost
... Show MoreThe problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline
... Show MoreIncreased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo
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