Machine learning has been useful for prediction in the various sectors of economy. The research work proposed an ensemble SA-CCT machine algorithm that gives early and accurate blackpod disease to farmers agricultural extension officers South-West, Nigeria. Since data mining put into consideration types pattern a given dataset, study considered climatic dataset retrieved from Nigeria Meteorolog...

This study compared the methods used to forecast increases in power consumption caused by rising popularity of electric vehicles (EVs). An excellent model for each region was proposed using multiple scaled geographical datasets over two years. EV charging volumes are influenced various factors, including condition a vehicle, battery’s state-of-charge (SOC), and distance destination. However, su...

Sugarcane industry is of crucial importance to the South Asian countries. These countries depend heavily on agriculture and sugarcane has immense potential contribute towards its economic development. Hence, precise timely forecast production concern for farmers, policy makers other stakeholders. In this manuscript, we strived growth rate important commodity using standard statistical approache...

Harvesting energy from solar radiation has emerged as an effective approach to prolong the lifetime of outdoor harvesting sensor networks. The harvested must be carefully managed ensure that sufficient is available when scarce. For prediction problem power harvesting, this paper proposes adaptive seasonal auto-regressive integrated moving average model (ASARIMA) for prediction. A training set c...

In this paper, we present a novel approach to estimate traffic speed using a sequence of images from an uncalibrated camera. We assert that exact calibration is not necessary to estimate speed. Instead, we use 1) geometric relationships inherently available in the image, 2) some common-sense assumptions that reduce the problem to a one-dimensional (1-D) geometry, 3) frame differencing to isolat...

To investigate the applicability of ARIMA models in wholesale vegetable market models are built taking sales data of one perishable vegetable from Ahmedabad wholesales market in India. It is found that these models can be applied to forecast the demand with Mean Absolute Percentage Error (MAPE) in the range of 30%. This error is acceptable in fresh produce market where the demand and prices are...

Energy consumption is vital to the global costs of wastewater treatment plants (WWTPs). With increase installed WWTPs worldwide, modeling and forecast their energy have become a critical factor in WWTP design meet environmental economic requirements. The accurate swift forecasting soft-sensors are not only supportive daily electric financial budgeting by practitioners on micro-scale, but also b...

Abstract: In this paper we discuss a two model multilayer neural network controller for adaptive control of blood pressure using sodium nitroprusside. A model with auto-regressive moving average, represent the dynamics of the system and a modified backpropagation training algorithm are used to design the control system to meet specified objectives of design and clinical constraints. Controller ...

This study develops a sedimentation process model that simulate the effects of inflow water quality, treatment flow rate and outflow water quality. The model uses transfer function ARIMA (Auto-Regressive Moving Average) for reflecting the dynamic characteristics of the system The sedimentation model for outflow water turbidity are separated into low and high turbidity by input variables, turbid...