Chicken Swarm Optimization algorithm for feature selection is proposed in this paper, which can be used for the prediction of cervical cancer. Cervical Cancer is the type of cancer that occurs at the cells of the cervix-the lower part of the uterus-which connects the vagina. This kind of cancer is generally caused by several strains of the human papillomavirus (HPV), a sexually transmitted infection. Feature Selection is a tool of optimization algorithm and plays an active role in the area of machine learning. The amount of data available for processing in machine learning problems has increased rapidly in recent years. So, the feature selection was introduced to solve this problem. Feature Selection is used when there is a need to eliminate such redundant features so that a better subset of features can be obtained by which dimensionality of dataset is reduced considerably. The Chicken Swarm Optimization is an algorithm method inspired by nature, which is used for optimization techniques, proposed for feature selection for prediction of cervical cancer. Impersonating the hierarchical order in the Chicken Swarm, which includes hens, roosters, and chicks. CSO can productively extricate the chickens' swarm intelligence to optimize problems. CSO has the ability to attain exceptional optimization results in terms of optimization correctness. In CSO, the chicken swarm is divided into various sets or groups, which consist of a single rooster and a number of hens

The pros and cons of using the bioremediation method for the removal of petroleum pollutants are discussed in this review article. Other methods along with bioremediation have been used to remediate petroleum hydrocarbon contaminants in the past. Bioremediation is cheap and efficient method than any other because major constituents of the crude oils are biodegradable. Despite the fact that, as compared to physicochemical strategies, longer periods are normally required, complete pollutant degradation can be achieved, and no further containment of the contaminated matrix is required. According to hydrocarbon present in the contaminants different strategies and organism are used for the bioremediation. Common strategies include controlling environmental factors such as oxygen availability, hydrocarbon solubility, nutrient balance and managing hydrocarbon degrading bacteria by eliminating the rate limiting factors that may slow down the bioremediation rate. Microorganism dynamics during bioremediation is most important for understanding how they respond, adapt and remediate pollution. However, bioremediation can be considered one of the best technologies to deal with petroleum product contaminants.

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