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 Tre

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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but  in this paper, the researcher proposed five pile types, one of them is not a traditional, and   developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with t

Bendable concrete, also known as Engineered Cementitious Composite (ECC) is a type of ultra-ductile cementitious composites reinforced with fibres to control the width of cracks. It has the ability to enhance concrete flexibility by withstanding strains of 3% and higher. The properties of bendable concrete mixes (compressive strength, flexural strength, and drying shrinkage) are here assessed after the incorporation of supplementary cementitious materials, silica fume, polymer fibres, and the use of ordinary Portland cement (O.P.C) and Portland limestone cement (IL). Mixes with Portland limestone cement show lower drying shrinkage and lower compressive and flexural strength than mixes with ordinary Portland cement, due to the ratio o

Conventional concretes are almost unbending, and even a small amount of strain potential leaves them brittle. This lack of bendability is a major source of strain loss, and it has been the main goal behind the development of bendable concrete, often known with engineered ce ment composites, or ECC. This form of concrete has a lot more flexibility than regular concrete. Micromechanical polymer fibers are used to strengthen ECC. In most cases, ECC uses a 2% amount of thin, separated fibers. As a result, bendable concrete deforms but unlike traditional concrete, it does not crack. This study aims to include this kind of concrete, bendable concrete, which can be used to solve concrete problems. Karasta (CK) and Tasluja (CT) Portland Lime

Conventional concretes are nearly unbendable, and just 0.1 percent of strain potential makes them incredibly brittle and stiff. This absence of bendability is a significant cause of strain failure and has been a guiding force in the production of an elegant substance, bendable concrete, also known as engineered cement composites, abbreviated as ECC. This type of concrete is capable of displaying dramatically increased flexibility. ECC is reinforced with micromechanical polymer fibers. ECC usually uses a 2 percent volume of small, disconnected fibers. Thus, bendable concrete deforms but without breaking any further than conventional concrete. This research aims to involve this type of concrete, bendable concrete, that will give solut