Risk Assessment Model for Pluvial Flood Prediction Using Fuzzy-Based Classification Technique

Both developed and developing countries are promoting risk management and refining the ability to alleviate the effects of disaster both man-made and natural, which have become a threat to human life and the world’s economy. The variability in climate change, rapid urbanization and fast-growing socio-economic development has naturally increased the risk associated with flooding. A recent report showed that flood have affected more individuals than any other category of disaster in the 21st century with the highest percentage of 43% of all disaster events in 2019 and Africa been the second vulnerable continent after Asia. So, it is highly important to devise a scientific method for flood risk reduction since it cannot be eradicated. Machine learning can improve the risk management. The paper proposes a pluvial flood detection and prediction system based on machine learning techniques. The proposed model will employ a fuzzy rule-based classification approach for pluvial flood risk assessment. Keywords: Machine Learning, Pluvial Flood, Risk, Fuzzy Rule-Based, Prediction DOI: 10.7176/CEIS/12-1-07 Publication date: January 31st 202

Potential of Breadfruit Meal as Alternative Energy Source to Maize in Diet of Broiler Chickens

This study was conducted to investigate the response of broiler chickens to diets containing breadfruit meal (BFM). Two hundred and fifty-six (256) day-old unsexed Anak 2000 broiler chicks were randomly allotted to the eight dietary treatments consisting of four replicates of eight chicks each. The experimental layout was a 2×4 factorial arrangement with two types of breadfruit meal (raw and cooked breadfruit meal) and four levels (0, 10, 20, 30%) of each BFM (Table 2). The diets were balanced for energy and crude protein. Cooking of the BFM increased (P<0.05) daily weight gain of birds while it decreased (P<0.05) with increase in inclusion level of BFM. The interaction between processing and inclusion levels of BFM was significant (P<0.05) for daily weight gain, feed/gain and protein efficiency ratio. Crude fibre (CF), ash and nitrogen free extract (NFE) digestibility reduced (P<0.05) in cooked BFM diets while inclusion of BFM increased the NFE digestibility and reduced ash digestibility. Processing of BFM had no effect (P>0.05) on the measured serum metabolites except serum glutamate pyruvate transaminase (SGPT) which was reduced (P<0.05) with processing of BFM. Uric acid decreased (P<0.05) while globulin increased (P<0.05) with increased inclusion level of BFM. Relative weights of breast muscle, drumstick and thigh were higher in birds fed cooked BFM. Total cost of feed consumed per bird and cost of feed per kg weight gain decreased (P<0.05) in the BFM diets. Total cost of feed consumed per bird was higher (P<0.05) in cooked BFM but the cost of feed per kg weight gain decreased (P<0.05) in the cooked BFM