Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Trees (DT), K- nearest neighbor (KNN), and Logistic Regression (LR), have been used to identify the parameters that allow for effective price estimation. These approaches were tested on a data set of an extensive Indian airline network. When it came to estimating flight prices, the results demonstrate that the Decision tree method is the best conceivable Algorithm for predicting the price of a flight in our particular situation with 89% accuracy. The SGD method had the lowest accuracy, which was 38 %, while the accuracies of the KNN, NB, ADA, and LR algorithms were 69 %, 45 %, and 43 %, respectively. This study's presented methodologies will allow airline firms to predict flight prices more accurately, enhance air travel, and eliminate delay dispersion.
(108)
(91)
(14)
Reactive Powder Concrete (RPC) can be incorporate as a one of the most important and progressive concrete technology. It is a special type of ultra-high strength concrete (UHSC) that’s exclude the coarse aggregate from its constitutive materials. In this research an experimental study had been carried out to investigate the effect of using three types of materials (porcelain aggregate) and others sustainable materials (glass waste and granular activated carbon) as a partial replacement of fine aggregate. Four percentages had considered (0, 10, 15 and 20) % to achieve better understanding for the influence of these materials upon the compressive strength of RPC. Four curing ages had included in this study, these are; 7, 28, 60 and
... Show More
(8)
The COVID-19 pandemic has deeply affected the respiratory health of people, leaving many sufferers with long term pulmonary problems. Artificial intelligence based physiological analysis of structured exercise program on lung function of recovered COVID 19 patient is studied. The research introduces an integrated data driven approach for assessing the improvement of respiratory through physical training. The approach is to integrate wearable sensor technology with machine learning algorithms. A controlled experimental study with three groups (recovered COVID-19 patients, smokers, healthy individuals) was used as a method. To that aim, each of the participants underwent an eight-week structured aerobic training program that included continuo
... Show More
Temporomandibular Disorders (TMD) refer to a group of symptoms where pain is the most leading cause to demand a treatment by the patient. Light therapies are of great importance at current times due to its biosafety and non-invasive quality when used for the management of TMD symptoms. This study aimed to evaluate the efficacy of red LED light with low-level LASER in treating TMD patients.
A double-blind randomized clinical study was conducted and included 60 patients along 3 groups (20 for e
(19)
(22)
(14)
(7)
(10)
(12)
The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c
... Show More
(44)
(36)
(2)
(2)
A mathematical model constructed to study the combined effects of the concentration and the thermodiffusion on the nanoparticles of a Jeffrey fluid with a magnetic field effect the process of containing waves in a three-dimensional rectangular porous medium canal. Using the HPM to solve the nonlinear and coupled partial differential equations. Numerical results were obtained for temperature distribution, nanoparticles concentration, velocity, pressure rise, pressure gradient, friction force and stream function. Through the graphs, it was found that the velocity of fluid rises with the increase of a mean rate of volume flow and a magnetic parameter, while the velocity goes down with the increasing a Darcy number and lateral walls. Also, t
... Show More
(6)
(1)